Decision Tree in Python
Train Decision Tree in Python. Algorithm can be used in classification and regression tasks. Please make sure that there are no missing values in the training data and all values are numeric.
Please check Advanced options. There are several criterions available to measure split quality. What is more, you can control the tree structure by selecting minimum number of samples for internal node split and minimum samples in the leaf. The max depth parameter controls the depth of the tree, if it is not set then tree is trained till all leaves are pure or there are minimum samples in the internal node.
Decision Tree model can be persisted to hard disk in pickle format.
Required packages
You need below packages to use the code generated by recipe. All packages are automatically installed in MLJAR Studio.
scikit-learn>=1.5.0
Interactive recipe
You can use below interactive recipe to generate code. This recipe is available in MLJAR Studio.
Python code
# Python code will be here
Code explanation
This code recipe initialize Decision Tree object. It is ready to fit or tunning.
Fitted object can be used to compute predictions. If you want to persist your Decision Tree, please save it to pickle file (Save to pickle recipe).
Example Python notebooks
Please find inspiration in example notebooks
- Visualize Decision Tree
The Decision Tree algorithm's structure is human-readable, a key advantage. In ...
- Decision Tree features importance
`Scikit-learn's` permutation importance assesses the impact of each feature on ...
- Train Decision Tree classifier
Classification is a task of predicting discrete target labels. The Python `scikit-learn` ...
- Train Decision Tree on Iris data set
Python is a great choice for Machine Learning projects, because of rich ML packages ...
- Train Decision Tree regressor
Train a Decision Tree Regressor using scikit-learn. This machine learning algorithm ...
- Save and load Decision Tree
`Scikit-learn` provides Decision Tree algorithms for classification (`DecisionTreeClassifier`) ...
- Tune Decision Tree classifier
This notebook demonstrates tuning a Decision Tree model. We'll find the best hyperparameters ...
Scikit-learn cookbook
Code recipes from Scikit-learn cookbook.
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