A decision tree is a decision support tool that uses a tree-like model of decisions and their possible consequences
in this vide you will learn below topics on how to prune decision tree
00:00 what is overfitting
02:00 why decision tree is prone to overfitting
03:52 What is pre pruning in decision trees?
04:57 pre pruning using max depth
06:03 pre pruning using max leaf sample
08:28 pre pruning using max leaf node
09:10 Issue in pre pruning ?
10:26 cancer detection model using sklearn
16:16 graphviz to visualize decision tree
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introduction,How to construct decision tree,root node vs decision node vs leaf node ,how to make prediction with decision tree ,binary vs non binary conditions , ID3 vs c4.5 vs CART,how to choose the root name ,how to chose the decision node ,measure quality of split using gini or entropy ,advantages and disadvantages of decision tree , what is gini,what is entropy,How to select Best Split in Decision trees using Gini Impurity,How to select Best Split in Decision trees using Entropy , How to select Best Split in Decision trees , gini vs entropy, gini gain,information gain , gini gain vs information gain,machinelearningintamil ,machinelearning in tamil ,machinelearningtamil,machinelearningintamil tutorials,machinelearningintamil course,Decision trees
Pre-pruning,
Tree pruning,
Machine learning,
Data mining,
Classification,
Regression,
Overfitting
Underfitting
#decisiontree #machinelearningintamil #machinelearning #pythonfordatascience #datascience