Skip to content

This repository contains Machine Learning Lab cycle programs.

Notifications You must be signed in to change notification settings

kramachandrashenoy/ML-Lab

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

ML Lab

Programs for Machine Learning Lab internals (20CS67L)

1 Visualize the n-dimensional data using 3D surface plots. Write a program to implement the Best First Search (BFS) algorithm.

2 Visualize the n-dimensional data using contour plots. Write a program to implement the A* algorithm

3 Visualize the n-dimensional data using heat-map. Write a program to implement Min-Max algorithm.

4 Visualize the n-dimensional data using Box-plot. Write a program to implement Alpha-beta pruning algorithm.

5 Write a program to develop the Naive Bayes classifier on Titanic dataset.

6 Write a program to develop the KNN classifier with Euclidean distance and Manhattan distance for the k values as 3 based on split up of training and testing dataset as 70-30 on Glass dataset.

7 Write a program to develop a decision tree classifier based on weather forecasting dataset.

8 Write a program to perform unsupervised K-means clustering techniques on Iris dataset.

9 Write a program to perform agglomerative clustering based on single-linkage, complete-linkage criteria.

10 Write a program to develop a decision tree classifier based on weather forecasting dataset.

11 Write a program to develop Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) algorithms.

About

This repository contains Machine Learning Lab cycle programs.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published