Supervised learning

Supervised learning

1. Classification

2. Regression

3. Decision Trees

   • min_samples_split
   • Entropy & Information gain
   • Bias & Variance
   • DecisionTreeClassifier
   • DecisionTreeRegressor

4. Neural networks

   • Perceptron
     • Basic logic functions
       • OR
       • AND
       • NOT
     • Training
       • Perceptron rule
         • Finds a plane for linearly separable dataset.
       • Gradient descent
       • Back propagation (sigmoid)
   • Restriction bias
   • Preference bias

5. Support vector machine

   • Maximize the margin

6. Ensemble methods

   • Bagging
     • Random forrests
     • Extremely Randomized Trees
   • Boosting