Commit 8d38be06 authored by Olivier Michel's avatar Olivier Michel 💬
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# Lab 8 statement
The objective of this lab is to illustrate Tree based classification and regression methods. Forest trees are introduced as a natural bagging method.
_Note: For each notebook, read the cells and run the code, then follow the instructions/questions in the questions` or `Exercise` cells._`
See the notebooks in the [`8_Trees_Boosting`]( folder
1. Firsts steps with classification trees [`N1_Classif_tree.ipynb`](
2. Examples of regression trees [`N2_a_Regression_tree.ipynb`]( and cost complexity pruning methods [`N2_b_Cost_Complexity_Pruning_Regressor.ipynb`](
3.The 3 notebooks below illstrate the concept of bagging through the application of random forests
4. Implement your own version of EM for Gaussian model and apply it to the same example used for Kmeans in a preceeding notebook. Compare with KMeans and interpret the results [`N2_a_Regression_tree.ipynb`](
5. Example of EM application on the Iris data set [`N2_a_Regression_tree.ipynb`](
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