train DecisionTree on multiple records

rageSpin · Feb 12, 2023 · 5986abf · 5986abf
1 parent feaabfb
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diff --git a/Reinforcement Learning/CartPole/cartpole-DQN.py b/Reinforcement Learning/CartPole/cartpole-DQN.py
@@ -59,7 +59,7 @@ def experience_replay(self):
             q_values[0][action] = q_update
             #print(state.shape, q_values.shape)
             x[i], y[i] = state, q_values
-        self.model.fit(x, y, verbose=0, epochs=10)
+        self.model.fit(x, y, verbose=0, epochs=3)
         self.exploration_rate *= EXPLORATION_DECAY
         self.exploration_rate = max(EXPLORATION_MIN, self.exploration_rate)
 
@@ -92,7 +92,6 @@ def cartpole():
                 dqn_solver.experience_replay()
                 break
 
-
         if run > 1000:
             break
 

diff --git a/Reinforcement Learning/CartPole/cartpole-simple_physics.ipynb b/Reinforcement Learning/CartPole/cartpole-simple_physics.ipynb