model.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import librosa, librosa.display\n",
    "import IPython.display as ipd\n",
    "import math\n",
    "import json \n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('./data/features_30_sec.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>filename</th>\n",
       "      <th>length</th>\n",
       "      <th>chroma_stft_mean</th>\n",
       "      <th>chroma_stft_var</th>\n",
       "      <th>rms_mean</th>\n",
       "      <th>rms_var</th>\n",
       "      <th>spectral_centroid_mean</th>\n",
       "      <th>spectral_centroid_var</th>\n",
       "      <th>spectral_bandwidth_mean</th>\n",
       "      <th>spectral_bandwidth_var</th>\n",
       "      <th>...</th>\n",
       "      <th>mfcc16_var</th>\n",
       "      <th>mfcc17_mean</th>\n",
       "      <th>mfcc17_var</th>\n",
       "      <th>mfcc18_mean</th>\n",
       "      <th>mfcc18_var</th>\n",
       "      <th>mfcc19_mean</th>\n",
       "      <th>mfcc19_var</th>\n",
       "      <th>mfcc20_mean</th>\n",
       "      <th>mfcc20_var</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>blues.00000.wav</td>\n",
       "      <td>661794</td>\n",
       "      <td>0.350088</td>\n",
       "      <td>0.088757</td>\n",
       "      <td>0.130228</td>\n",
       "      <td>0.002827</td>\n",
       "      <td>1784.165850</td>\n",
       "      <td>129774.064525</td>\n",
       "      <td>2002.449060</td>\n",
       "      <td>85882.761315</td>\n",
       "      <td>...</td>\n",
       "      <td>52.420910</td>\n",
       "      <td>-1.690215</td>\n",
       "      <td>36.524071</td>\n",
       "      <td>-0.408979</td>\n",
       "      <td>41.597103</td>\n",
       "      <td>-2.303523</td>\n",
       "      <td>55.062923</td>\n",
       "      <td>1.221291</td>\n",
       "      <td>46.936035</td>\n",
       "      <td>blues</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>blues.00001.wav</td>\n",
       "      <td>661794</td>\n",
       "      <td>0.340914</td>\n",
       "      <td>0.094980</td>\n",
       "      <td>0.095948</td>\n",
       "      <td>0.002373</td>\n",
       "      <td>1530.176679</td>\n",
       "      <td>375850.073649</td>\n",
       "      <td>2039.036516</td>\n",
       "      <td>213843.755497</td>\n",
       "      <td>...</td>\n",
       "      <td>55.356403</td>\n",
       "      <td>-0.731125</td>\n",
       "      <td>60.314529</td>\n",
       "      <td>0.295073</td>\n",
       "      <td>48.120598</td>\n",
       "      <td>-0.283518</td>\n",
       "      <td>51.106190</td>\n",
       "      <td>0.531217</td>\n",
       "      <td>45.786282</td>\n",
       "      <td>blues</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>blues.00002.wav</td>\n",
       "      <td>661794</td>\n",
       "      <td>0.363637</td>\n",
       "      <td>0.085275</td>\n",
       "      <td>0.175570</td>\n",
       "      <td>0.002746</td>\n",
       "      <td>1552.811865</td>\n",
       "      <td>156467.643368</td>\n",
       "      <td>1747.702312</td>\n",
       "      <td>76254.192257</td>\n",
       "      <td>...</td>\n",
       "      <td>40.598766</td>\n",
       "      <td>-7.729093</td>\n",
       "      <td>47.639427</td>\n",
       "      <td>-1.816407</td>\n",
       "      <td>52.382141</td>\n",
       "      <td>-3.439720</td>\n",
       "      <td>46.639660</td>\n",
       "      <td>-2.231258</td>\n",
       "      <td>30.573025</td>\n",
       "      <td>blues</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>blues.00003.wav</td>\n",
       "      <td>661794</td>\n",
       "      <td>0.404785</td>\n",
       "      <td>0.093999</td>\n",
       "      <td>0.141093</td>\n",
       "      <td>0.006346</td>\n",
       "      <td>1070.106615</td>\n",
       "      <td>184355.942417</td>\n",
       "      <td>1596.412872</td>\n",
       "      <td>166441.494769</td>\n",
       "      <td>...</td>\n",
       "      <td>44.427753</td>\n",
       "      <td>-3.319597</td>\n",
       "      <td>50.206673</td>\n",
       "      <td>0.636965</td>\n",
       "      <td>37.319130</td>\n",
       "      <td>-0.619121</td>\n",
       "      <td>37.259739</td>\n",
       "      <td>-3.407448</td>\n",
       "      <td>31.949339</td>\n",
       "      <td>blues</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>blues.00004.wav</td>\n",
       "      <td>661794</td>\n",
       "      <td>0.308526</td>\n",
       "      <td>0.087841</td>\n",
       "      <td>0.091529</td>\n",
       "      <td>0.002303</td>\n",
       "      <td>1835.004266</td>\n",
       "      <td>343399.939274</td>\n",
       "      <td>1748.172116</td>\n",
       "      <td>88445.209036</td>\n",
       "      <td>...</td>\n",
       "      <td>86.099236</td>\n",
       "      <td>-5.454034</td>\n",
       "      <td>75.269707</td>\n",
       "      <td>-0.916874</td>\n",
       "      <td>53.613918</td>\n",
       "      <td>-4.404827</td>\n",
       "      <td>62.910812</td>\n",
       "      <td>-11.703234</td>\n",
       "      <td>55.195160</td>\n",
       "      <td>blues</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>rock.00095.wav</td>\n",
       "      <td>661794</td>\n",
       "      <td>0.352063</td>\n",
       "      <td>0.080487</td>\n",
       "      <td>0.079486</td>\n",
       "      <td>0.000345</td>\n",
       "      <td>2008.149458</td>\n",
       "      <td>282174.689224</td>\n",
       "      <td>2106.541053</td>\n",
       "      <td>88609.749506</td>\n",
       "      <td>...</td>\n",
       "      <td>45.050526</td>\n",
       "      <td>-13.289984</td>\n",
       "      <td>41.754955</td>\n",
       "      <td>2.484145</td>\n",
       "      <td>36.778877</td>\n",
       "      <td>-6.713265</td>\n",
       "      <td>54.866825</td>\n",
       "      <td>-1.193787</td>\n",
       "      <td>49.950665</td>\n",
       "      <td>rock</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>rock.00096.wav</td>\n",
       "      <td>661794</td>\n",
       "      <td>0.398687</td>\n",
       "      <td>0.075086</td>\n",
       "      <td>0.076458</td>\n",
       "      <td>0.000588</td>\n",
       "      <td>2006.843354</td>\n",
       "      <td>182114.709510</td>\n",
       "      <td>2068.942009</td>\n",
       "      <td>82426.016726</td>\n",
       "      <td>...</td>\n",
       "      <td>33.851742</td>\n",
       "      <td>-10.848309</td>\n",
       "      <td>39.395096</td>\n",
       "      <td>1.881229</td>\n",
       "      <td>32.010040</td>\n",
       "      <td>-7.461491</td>\n",
       "      <td>39.196327</td>\n",
       "      <td>-2.795338</td>\n",
       "      <td>31.773624</td>\n",
       "      <td>rock</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>rock.00097.wav</td>\n",
       "      <td>661794</td>\n",
       "      <td>0.432142</td>\n",
       "      <td>0.075268</td>\n",
       "      <td>0.081651</td>\n",
       "      <td>0.000322</td>\n",
       "      <td>2077.526598</td>\n",
       "      <td>231657.968040</td>\n",
       "      <td>1927.293153</td>\n",
       "      <td>74717.124394</td>\n",
       "      <td>...</td>\n",
       "      <td>33.597008</td>\n",
       "      <td>-12.845291</td>\n",
       "      <td>36.367264</td>\n",
       "      <td>3.440978</td>\n",
       "      <td>36.001110</td>\n",
       "      <td>-12.588070</td>\n",
       "      <td>42.502201</td>\n",
       "      <td>-2.106337</td>\n",
       "      <td>29.865515</td>\n",
       "      <td>rock</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>rock.00098.wav</td>\n",
       "      <td>661794</td>\n",
       "      <td>0.362485</td>\n",
       "      <td>0.091506</td>\n",
       "      <td>0.083860</td>\n",
       "      <td>0.001211</td>\n",
       "      <td>1398.699344</td>\n",
       "      <td>240318.731073</td>\n",
       "      <td>1818.450280</td>\n",
       "      <td>109090.207161</td>\n",
       "      <td>...</td>\n",
       "      <td>46.324894</td>\n",
       "      <td>-4.416050</td>\n",
       "      <td>43.583942</td>\n",
       "      <td>1.556207</td>\n",
       "      <td>34.331261</td>\n",
       "      <td>-5.041897</td>\n",
       "      <td>47.227180</td>\n",
       "      <td>-3.590644</td>\n",
       "      <td>41.299088</td>\n",
       "      <td>rock</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>rock.00099.wav</td>\n",
       "      <td>661794</td>\n",
       "      <td>0.358401</td>\n",
       "      <td>0.085884</td>\n",
       "      <td>0.054454</td>\n",
       "      <td>0.000336</td>\n",
       "      <td>1609.795082</td>\n",
       "      <td>422203.216152</td>\n",
       "      <td>1797.213044</td>\n",
       "      <td>120115.632927</td>\n",
       "      <td>...</td>\n",
       "      <td>59.167755</td>\n",
       "      <td>-7.069775</td>\n",
       "      <td>73.760391</td>\n",
       "      <td>0.028346</td>\n",
       "      <td>76.504326</td>\n",
       "      <td>-2.025783</td>\n",
       "      <td>72.189316</td>\n",
       "      <td>1.155239</td>\n",
       "      <td>49.662510</td>\n",
       "      <td>rock</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 60 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            filename  length  chroma_stft_mean  chroma_stft_var  rms_mean  \\\n",
       "0    blues.00000.wav  661794          0.350088         0.088757  0.130228   \n",
       "1    blues.00001.wav  661794          0.340914         0.094980  0.095948   \n",
       "2    blues.00002.wav  661794          0.363637         0.085275  0.175570   \n",
       "3    blues.00003.wav  661794          0.404785         0.093999  0.141093   \n",
       "4    blues.00004.wav  661794          0.308526         0.087841  0.091529   \n",
       "..               ...     ...               ...              ...       ...   \n",
       "995   rock.00095.wav  661794          0.352063         0.080487  0.079486   \n",
       "996   rock.00096.wav  661794          0.398687         0.075086  0.076458   \n",
       "997   rock.00097.wav  661794          0.432142         0.075268  0.081651   \n",
       "998   rock.00098.wav  661794          0.362485         0.091506  0.083860   \n",
       "999   rock.00099.wav  661794          0.358401         0.085884  0.054454   \n",
       "\n",
       "      rms_var  spectral_centroid_mean  spectral_centroid_var  \\\n",
       "0    0.002827             1784.165850          129774.064525   \n",
       "1    0.002373             1530.176679          375850.073649   \n",
       "2    0.002746             1552.811865          156467.643368   \n",
       "3    0.006346             1070.106615          184355.942417   \n",
       "4    0.002303             1835.004266          343399.939274   \n",
       "..        ...                     ...                    ...   \n",
       "995  0.000345             2008.149458          282174.689224   \n",
       "996  0.000588             2006.843354          182114.709510   \n",
       "997  0.000322             2077.526598          231657.968040   \n",
       "998  0.001211             1398.699344          240318.731073   \n",
       "999  0.000336             1609.795082          422203.216152   \n",
       "\n",
       "     spectral_bandwidth_mean  spectral_bandwidth_var  ...  mfcc16_var  \\\n",
       "0                2002.449060            85882.761315  ...   52.420910   \n",
       "1                2039.036516           213843.755497  ...   55.356403   \n",
       "2                1747.702312            76254.192257  ...   40.598766   \n",
       "3                1596.412872           166441.494769  ...   44.427753   \n",
       "4                1748.172116            88445.209036  ...   86.099236   \n",
       "..                       ...                     ...  ...         ...   \n",
       "995              2106.541053            88609.749506  ...   45.050526   \n",
       "996              2068.942009            82426.016726  ...   33.851742   \n",
       "997              1927.293153            74717.124394  ...   33.597008   \n",
       "998              1818.450280           109090.207161  ...   46.324894   \n",
       "999              1797.213044           120115.632927  ...   59.167755   \n",
       "\n",
       "     mfcc17_mean  mfcc17_var  mfcc18_mean  mfcc18_var  mfcc19_mean  \\\n",
       "0      -1.690215   36.524071    -0.408979   41.597103    -2.303523   \n",
       "1      -0.731125   60.314529     0.295073   48.120598    -0.283518   \n",
       "2      -7.729093   47.639427    -1.816407   52.382141    -3.439720   \n",
       "3      -3.319597   50.206673     0.636965   37.319130    -0.619121   \n",
       "4      -5.454034   75.269707    -0.916874   53.613918    -4.404827   \n",
       "..           ...         ...          ...         ...          ...   \n",
       "995   -13.289984   41.754955     2.484145   36.778877    -6.713265   \n",
       "996   -10.848309   39.395096     1.881229   32.010040    -7.461491   \n",
       "997   -12.845291   36.367264     3.440978   36.001110   -12.588070   \n",
       "998    -4.416050   43.583942     1.556207   34.331261    -5.041897   \n",
       "999    -7.069775   73.760391     0.028346   76.504326    -2.025783   \n",
       "\n",
       "     mfcc19_var  mfcc20_mean  mfcc20_var  label  \n",
       "0     55.062923     1.221291   46.936035  blues  \n",
       "1     51.106190     0.531217   45.786282  blues  \n",
       "2     46.639660    -2.231258   30.573025  blues  \n",
       "3     37.259739    -3.407448   31.949339  blues  \n",
       "4     62.910812   -11.703234   55.195160  blues  \n",
       "..          ...          ...         ...    ...  \n",
       "995   54.866825    -1.193787   49.950665   rock  \n",
       "996   39.196327    -2.795338   31.773624   rock  \n",
       "997   42.502201    -2.106337   29.865515   rock  \n",
       "998   47.227180    -3.590644   41.299088   rock  \n",
       "999   72.189316     1.155239   49.662510   rock  \n",
       "\n",
       "[1000 rows x 60 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def ae(signal, frame_size, hop_length):\n",
    "    return np.array([max(signal[i:i+frame_size]) for i in range(0, signal.size, hop_length)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [],
   "source": [
    "def save_mfcc(dataset_path, json_path, n_mfcc=13, n_fft=2048,\n",
    "             hop_length=512, num_segments=5):\n",
    "    # Data storage dictionary\n",
    "    data = {\n",
    "        \"mapping\": [],\n",
    "        \"mfcc_1\": [],\n",
    "        \"mfcc_2\": [],\n",
    "        \"mfcc_3\": [],\n",
    "        \"mfcc_4\": [],\n",
    "        \"mfcc_5\": [],\n",
    "        \"mfcc_6\": [],\n",
    "        \"mfcc_7\": [],\n",
    "        \"mfcc_8\": [],\n",
    "        \"mfcc_9\": [],\n",
    "        \"mfcc_10\": [],\n",
    "        \"chroma_mean\": [],\n",
    "        \"chroma_std\": [],\n",
    "        \"rms_mean\": [],\n",
    "        \"rms_std\": [],\n",
    "        \"ae_mean\": [],\n",
    "        \"ae_std\": [],\n",
    "        \"zcr_mean\": [],\n",
    "        \"zcr_std\": [],\n",
    "        \"sc_mean\": [],\n",
    "        \"sc_std\": [],\n",
    "        \"band_mean\": [],\n",
    "        \"band_std\": [],\n",
    "        \"labels\": [],\n",
    "    }\n",
    "    samples_ps = int(SAMPLES_PER_TRACK/num_segments) # ps = per segment\n",
    "    expected_vects_ps = math.ceil(samples_ps/hop_length)\n",
    "    #\n",
    "    #count = 0\n",
    "    # loop through all the genres\n",
    "    for i, (dirpath, dirnames, filenames) in enumerate(os.walk(dataset_path)):\n",
    "        # ensuring not at root\n",
    "        \n",
    "        if dirpath is not dataset_path:\n",
    "            # save the semantic label\n",
    "            dirpath_comp = dirpath.split(\"/\")\n",
    "            semantic_label = dirpath_comp[-1]\n",
    "            data[\"mapping\"].append(semantic_label)\n",
    "            print(f\"Processing: {semantic_label}\")\n",
    "            count = 0\n",
    "            # process files for specific genre\n",
    "            for f in filenames:\n",
    "                if(f==str(\"jazz.00054.wav\")):\n",
    "                    # As librosa only read files <1Mb\n",
    "                    continue\n",
    "                else:\n",
    "                    # load audio file\n",
    "                    file_path = os.path.join(dirpath, f)\n",
    "                    signal,sr = librosa.load(file_path,sr=SAMPLE_RATE)\n",
    "                    \n",
    "                    chroma = librosa.feature.chroma_stft(signal,sr=sr)\n",
    "                    spectral_bandwidth = librosa.feature.spectral_bandwidth(y=signal, sr=sr, n_fft=n_fft, hop_length=hop_length)[0]\n",
    "                    spectral_centroid = librosa.feature.spectral_centroid(y=signal, sr=sr, n_fft=n_fft, hop_length=hop_length)[0]\n",
    "                    zcr = librosa.feature.zero_crossing_rate(signal, frame_length=n_fft, hop_length=hop_length)[0]\n",
    "                    ae_ = ae(signal, n_fft, hop_length)\n",
    "                    rms = librosa.feature.rms(signal, frame_length=n_fft, hop_length=hop_length)[0]\n",
    "\n",
    "                    data[\"chroma_mean\"].append(np.mean(chroma))\n",
    "                    data[\"chroma_std\"].append(np.std(chroma))\n",
    "                    data[\"rms_mean\"].append(np.mean(rms))\n",
    "                    data[\"rms_std\"].append(np.std(rms))\n",
    "                    data[\"ae_mean\"].append(np.mean(ae_))\n",
    "                    data[\"ae_std\"].append(np.std(ae_))\n",
    "                    data[\"zcr_mean\"].append(np.mean(zcr))\n",
    "                    data[\"zcr_std\"].append(np.std(zcr))\n",
    "                    data[\"sc_mean\"].append(np.mean(spectral_centroid))\n",
    "                    data[\"sc_std\"].append(np.std(spectral_centroid))\n",
    "                    data[\"band_mean\"].append(np.mean(spectral_bandwidth))\n",
    "                    data[\"band_std\"].append(np.std(spectral_bandwidth))\n",
    "                    data[\"labels\"].append(i-1)\n",
    "                    for s in range(num_segments):\n",
    "                        start_sample = samples_ps * s\n",
    "                        finish_sample = start_sample + samples_ps\n",
    "\n",
    "                        mfcc = librosa.feature.mfcc(signal,\n",
    "                                                    sr = sr,\n",
    "                                                    n_fft = n_fft,\n",
    "                                                    n_mfcc = n_mfcc,\n",
    "                                                    hop_length = hop_length)\n",
    "\n",
    "                        mfcc = mfcc.T\n",
    "                        \n",
    "                        \n",
    "                        # store featrues \n",
    "                        #if len(mfcc)==expected_vects_ps:\n",
    "                        string = 'mfcc_'+str(s+1)\n",
    "                        data[string].append(np.mean(mfcc[s]))\n",
    "                        #print(len(data[string]))\n",
    "                            #print(f\"{file_path}, segment: {s+1}\")\n",
    "                    \n",
    "                            \n",
    "                #count +=1\n",
    "                #if count ==  :break\n",
    "            #print(len(data[\"chroma_std\"]))\n",
    "            #print(len(data[\"rms_mean\"]))\n",
    "    del data['mapping']\n",
    "    dfobj = pd.DataFrame(data)\n",
    "    return dfobj"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processing: genres_original\\blues\n",
      "Processing: genres_original\\classical\n",
      "Processing: genres_original\\country\n",
      "Processing: genres_original\\disco\n",
      "Processing: genres_original\\hiphop\n",
      "Processing: genres_original\\jazz\n",
      "Processing: genres_original\\metal\n",
      "Processing: genres_original\\pop\n",
      "Processing: genres_original\\reggae\n",
      "Processing: genres_original\\rock\n"
     ]
    }
   ],
   "source": [
    "DATASET_PATH = './data/genres_original'\n",
    "JSON_PATH = 'data2.json'\n",
    "SAMPLE_RATE = 22050\n",
    "DURATION = 30\n",
    "SAMPLES_PER_TRACK = SAMPLE_RATE * DURATION\n",
    "df = save_mfcc(DATASET_PATH, JSON_PATH, num_segments=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mfcc_1</th>\n",
       "      <th>mfcc_2</th>\n",
       "      <th>mfcc_3</th>\n",
       "      <th>mfcc_4</th>\n",
       "      <th>mfcc_5</th>\n",
       "      <th>mfcc_6</th>\n",
       "      <th>mfcc_7</th>\n",
       "      <th>mfcc_8</th>\n",
       "      <th>mfcc_9</th>\n",
       "      <th>mfcc_10</th>\n",
       "      <th>...</th>\n",
       "      <th>rms_std</th>\n",
       "      <th>ae_mean</th>\n",
       "      <th>ae_std</th>\n",
       "      <th>zcr_mean</th>\n",
       "      <th>zcr_std</th>\n",
       "      <th>sc_mean</th>\n",
       "      <th>sc_std</th>\n",
       "      <th>band_mean</th>\n",
       "      <th>band_std</th>\n",
       "      <th>labels</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-5.706740</td>\n",
       "      <td>-4.415651</td>\n",
       "      <td>-1.091833</td>\n",
       "      <td>0.681720</td>\n",
       "      <td>3.644113</td>\n",
       "      <td>3.712207</td>\n",
       "      <td>2.797491</td>\n",
       "      <td>1.606959</td>\n",
       "      <td>0.651872</td>\n",
       "      <td>6.021034</td>\n",
       "      <td>...</td>\n",
       "      <td>0.053167</td>\n",
       "      <td>0.375375</td>\n",
       "      <td>0.140416</td>\n",
       "      <td>0.083045</td>\n",
       "      <td>0.027694</td>\n",
       "      <td>1784.165850</td>\n",
       "      <td>360.241675</td>\n",
       "      <td>2002.449060</td>\n",
       "      <td>293.057608</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-9.150007</td>\n",
       "      <td>1.682613</td>\n",
       "      <td>8.894200</td>\n",
       "      <td>9.854056</td>\n",
       "      <td>8.249156</td>\n",
       "      <td>5.946903</td>\n",
       "      <td>5.074986</td>\n",
       "      <td>3.307401</td>\n",
       "      <td>1.777985</td>\n",
       "      <td>-0.543458</td>\n",
       "      <td>...</td>\n",
       "      <td>0.048711</td>\n",
       "      <td>0.288863</td>\n",
       "      <td>0.146209</td>\n",
       "      <td>0.056040</td>\n",
       "      <td>0.038046</td>\n",
       "      <td>1530.176679</td>\n",
       "      <td>613.066125</td>\n",
       "      <td>2039.036516</td>\n",
       "      <td>462.432433</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.781586</td>\n",
       "      <td>4.258162</td>\n",
       "      <td>4.403440</td>\n",
       "      <td>2.913624</td>\n",
       "      <td>1.507566</td>\n",
       "      <td>1.430652</td>\n",
       "      <td>0.921271</td>\n",
       "      <td>0.191817</td>\n",
       "      <td>0.910968</td>\n",
       "      <td>-1.295847</td>\n",
       "      <td>...</td>\n",
       "      <td>0.052401</td>\n",
       "      <td>0.501379</td>\n",
       "      <td>0.142431</td>\n",
       "      <td>0.076291</td>\n",
       "      <td>0.031731</td>\n",
       "      <td>1552.811865</td>\n",
       "      <td>395.559911</td>\n",
       "      <td>1747.702312</td>\n",
       "      <td>276.141616</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7.084162</td>\n",
       "      <td>6.731664</td>\n",
       "      <td>5.285840</td>\n",
       "      <td>4.890325</td>\n",
       "      <td>4.167927</td>\n",
       "      <td>2.997913</td>\n",
       "      <td>2.814093</td>\n",
       "      <td>2.694005</td>\n",
       "      <td>1.904407</td>\n",
       "      <td>2.091464</td>\n",
       "      <td>...</td>\n",
       "      <td>0.079664</td>\n",
       "      <td>0.344977</td>\n",
       "      <td>0.179490</td>\n",
       "      <td>0.033309</td>\n",
       "      <td>0.020561</td>\n",
       "      <td>1070.106615</td>\n",
       "      <td>429.366909</td>\n",
       "      <td>1596.412872</td>\n",
       "      <td>407.972419</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-16.909956</td>\n",
       "      <td>-12.786216</td>\n",
       "      <td>-12.592538</td>\n",
       "      <td>-13.135061</td>\n",
       "      <td>-14.163464</td>\n",
       "      <td>-13.357795</td>\n",
       "      <td>-6.165907</td>\n",
       "      <td>-3.226989</td>\n",
       "      <td>-3.344306</td>\n",
       "      <td>-4.334365</td>\n",
       "      <td>...</td>\n",
       "      <td>0.047994</td>\n",
       "      <td>0.329738</td>\n",
       "      <td>0.173131</td>\n",
       "      <td>0.101461</td>\n",
       "      <td>0.044205</td>\n",
       "      <td>1835.004266</td>\n",
       "      <td>586.003361</td>\n",
       "      <td>1748.172116</td>\n",
       "      <td>297.397392</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>994</th>\n",
       "      <td>0.400775</td>\n",
       "      <td>-1.950820</td>\n",
       "      <td>-7.695916</td>\n",
       "      <td>-7.552310</td>\n",
       "      <td>-7.292852</td>\n",
       "      <td>-7.816775</td>\n",
       "      <td>-7.661562</td>\n",
       "      <td>-4.700060</td>\n",
       "      <td>-2.503638</td>\n",
       "      <td>-1.024971</td>\n",
       "      <td>...</td>\n",
       "      <td>0.018579</td>\n",
       "      <td>0.246240</td>\n",
       "      <td>0.075453</td>\n",
       "      <td>0.089227</td>\n",
       "      <td>0.036121</td>\n",
       "      <td>2008.149458</td>\n",
       "      <td>531.201176</td>\n",
       "      <td>2106.541053</td>\n",
       "      <td>297.673898</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>1.638267</td>\n",
       "      <td>-0.502136</td>\n",
       "      <td>-4.086061</td>\n",
       "      <td>-4.280716</td>\n",
       "      <td>-4.969070</td>\n",
       "      <td>-5.473058</td>\n",
       "      <td>-4.925173</td>\n",
       "      <td>-5.118340</td>\n",
       "      <td>-4.239804</td>\n",
       "      <td>-3.814622</td>\n",
       "      <td>...</td>\n",
       "      <td>0.024253</td>\n",
       "      <td>0.245862</td>\n",
       "      <td>0.092414</td>\n",
       "      <td>0.097664</td>\n",
       "      <td>0.029454</td>\n",
       "      <td>2006.843354</td>\n",
       "      <td>426.749001</td>\n",
       "      <td>2068.942009</td>\n",
       "      <td>287.099315</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>-4.131209</td>\n",
       "      <td>-3.784524</td>\n",
       "      <td>-2.548368</td>\n",
       "      <td>-1.603102</td>\n",
       "      <td>-2.815469</td>\n",
       "      <td>-3.741689</td>\n",
       "      <td>-3.820702</td>\n",
       "      <td>-6.226454</td>\n",
       "      <td>-7.538968</td>\n",
       "      <td>-7.905725</td>\n",
       "      <td>...</td>\n",
       "      <td>0.017954</td>\n",
       "      <td>0.263016</td>\n",
       "      <td>0.075060</td>\n",
       "      <td>0.121823</td>\n",
       "      <td>0.041192</td>\n",
       "      <td>2077.526598</td>\n",
       "      <td>481.308600</td>\n",
       "      <td>1927.293153</td>\n",
       "      <td>273.344333</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>3.436958</td>\n",
       "      <td>4.617150</td>\n",
       "      <td>4.031875</td>\n",
       "      <td>2.908208</td>\n",
       "      <td>1.277276</td>\n",
       "      <td>-0.212878</td>\n",
       "      <td>-1.490500</td>\n",
       "      <td>-0.958589</td>\n",
       "      <td>-0.353730</td>\n",
       "      <td>-0.274977</td>\n",
       "      <td>...</td>\n",
       "      <td>0.034800</td>\n",
       "      <td>0.237967</td>\n",
       "      <td>0.107956</td>\n",
       "      <td>0.048724</td>\n",
       "      <td>0.028417</td>\n",
       "      <td>1398.699344</td>\n",
       "      <td>490.223144</td>\n",
       "      <td>1818.450280</td>\n",
       "      <td>330.288067</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>-6.413524</td>\n",
       "      <td>-7.480601</td>\n",
       "      <td>-7.569191</td>\n",
       "      <td>-8.771984</td>\n",
       "      <td>-9.221186</td>\n",
       "      <td>-7.835105</td>\n",
       "      <td>-6.700880</td>\n",
       "      <td>-6.118079</td>\n",
       "      <td>-7.033674</td>\n",
       "      <td>-8.387018</td>\n",
       "      <td>...</td>\n",
       "      <td>0.018327</td>\n",
       "      <td>0.156700</td>\n",
       "      <td>0.072557</td>\n",
       "      <td>0.076305</td>\n",
       "      <td>0.046597</td>\n",
       "      <td>1609.795082</td>\n",
       "      <td>649.771665</td>\n",
       "      <td>1797.213044</td>\n",
       "      <td>346.577023</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>999 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        mfcc_1     mfcc_2     mfcc_3     mfcc_4     mfcc_5     mfcc_6  \\\n",
       "0    -5.706740  -4.415651  -1.091833   0.681720   3.644113   3.712207   \n",
       "1    -9.150007   1.682613   8.894200   9.854056   8.249156   5.946903   \n",
       "2     3.781586   4.258162   4.403440   2.913624   1.507566   1.430652   \n",
       "3     7.084162   6.731664   5.285840   4.890325   4.167927   2.997913   \n",
       "4   -16.909956 -12.786216 -12.592538 -13.135061 -14.163464 -13.357795   \n",
       "..         ...        ...        ...        ...        ...        ...   \n",
       "994   0.400775  -1.950820  -7.695916  -7.552310  -7.292852  -7.816775   \n",
       "995   1.638267  -0.502136  -4.086061  -4.280716  -4.969070  -5.473058   \n",
       "996  -4.131209  -3.784524  -2.548368  -1.603102  -2.815469  -3.741689   \n",
       "997   3.436958   4.617150   4.031875   2.908208   1.277276  -0.212878   \n",
       "998  -6.413524  -7.480601  -7.569191  -8.771984  -9.221186  -7.835105   \n",
       "\n",
       "       mfcc_7    mfcc_8    mfcc_9   mfcc_10  ...   rms_std   ae_mean  \\\n",
       "0    2.797491  1.606959  0.651872  6.021034  ...  0.053167  0.375375   \n",
       "1    5.074986  3.307401  1.777985 -0.543458  ...  0.048711  0.288863   \n",
       "2    0.921271  0.191817  0.910968 -1.295847  ...  0.052401  0.501379   \n",
       "3    2.814093  2.694005  1.904407  2.091464  ...  0.079664  0.344977   \n",
       "4   -6.165907 -3.226989 -3.344306 -4.334365  ...  0.047994  0.329738   \n",
       "..        ...       ...       ...       ...  ...       ...       ...   \n",
       "994 -7.661562 -4.700060 -2.503638 -1.024971  ...  0.018579  0.246240   \n",
       "995 -4.925173 -5.118340 -4.239804 -3.814622  ...  0.024253  0.245862   \n",
       "996 -3.820702 -6.226454 -7.538968 -7.905725  ...  0.017954  0.263016   \n",
       "997 -1.490500 -0.958589 -0.353730 -0.274977  ...  0.034800  0.237967   \n",
       "998 -6.700880 -6.118079 -7.033674 -8.387018  ...  0.018327  0.156700   \n",
       "\n",
       "       ae_std  zcr_mean   zcr_std      sc_mean      sc_std    band_mean  \\\n",
       "0    0.140416  0.083045  0.027694  1784.165850  360.241675  2002.449060   \n",
       "1    0.146209  0.056040  0.038046  1530.176679  613.066125  2039.036516   \n",
       "2    0.142431  0.076291  0.031731  1552.811865  395.559911  1747.702312   \n",
       "3    0.179490  0.033309  0.020561  1070.106615  429.366909  1596.412872   \n",
       "4    0.173131  0.101461  0.044205  1835.004266  586.003361  1748.172116   \n",
       "..        ...       ...       ...          ...         ...          ...   \n",
       "994  0.075453  0.089227  0.036121  2008.149458  531.201176  2106.541053   \n",
       "995  0.092414  0.097664  0.029454  2006.843354  426.749001  2068.942009   \n",
       "996  0.075060  0.121823  0.041192  2077.526598  481.308600  1927.293153   \n",
       "997  0.107956  0.048724  0.028417  1398.699344  490.223144  1818.450280   \n",
       "998  0.072557  0.076305  0.046597  1609.795082  649.771665  1797.213044   \n",
       "\n",
       "       band_std  labels  \n",
       "0    293.057608       0  \n",
       "1    462.432433       0  \n",
       "2    276.141616       0  \n",
       "3    407.972419       0  \n",
       "4    297.397392       0  \n",
       "..          ...     ...  \n",
       "994  297.673898       9  \n",
       "995  287.099315       9  \n",
       "996  273.344333       9  \n",
       "997  330.288067       9  \n",
       "998  346.577023       9  \n",
       "\n",
       "[999 rows x 23 columns]"
      ]
     },
     "execution_count": 160,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.naive_bayes import GaussianNB\n",
    "from sklearn.linear_model import SGDClassifier, LogisticRegression\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.neural_network import MLPClassifier\n",
    "\n",
    "from sklearn.metrics import confusion_matrix, accuracy_score, roc_auc_score, roc_curve\n",
    "from sklearn import preprocessing\n",
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = df.drop(['labels'],axis=1)\n",
    "y = df['labels'] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [],
   "source": [
    "cols = X.columns\n",
    "min_max_scaler = preprocessing.MinMaxScaler()\n",
    "np_scaled = min_max_scaler.fit_transform(X)\n",
    "\n",
    "# new data frame with the new scaled data. \n",
    "X = pd.DataFrame(np_scaled, columns = cols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((699, 22), (300, 22), (699,), (300,))"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=111)\n",
    "X_train.shape, X_test.shape, y_train.shape, y_test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [],
   "source": [
    "def model_assess(model, title = \"Default\"):\n",
    "    model.fit(X_train, y_train)\n",
    "    preds = model.predict(X_test)\n",
    "    #print(confusion_matrix(y_test, preds))\n",
    "    print('Accuracy', title, ':', round(accuracy_score(y_test, preds), 5), '\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy RFC : 0.58 \n",
      "\n",
      "Accuracy Support Vector Machine : 0.55 \n",
      "\n",
      "Accuracy Logistic Regression : 0.5 \n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\homep\\Anaconda3\\envs\\py37\\lib\\site-packages\\sklearn\\linear_model\\_logistic.py:764: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  extra_warning_msg=_LOGISTIC_SOLVER_CONVERGENCE_MSG)\n"
     ]
    }
   ],
   "source": [
    "# Random Forest Classifier\n",
    "RFC = RandomForestClassifier()\n",
    "model_assess(RFC, \"RFC\")\n",
    "\n",
    "# Support Vector Machine\n",
    "svm = SVC(decision_function_shape=\"ovo\")\n",
    "model_assess(svm, \"Support Vector Machine\")\n",
    "\n",
    "# Logistic Regression\n",
    "lg = LogisticRegression()\n",
    "model_assess(lg, \"Logistic Regression\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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