Python Scikit-Learn: Code & Plot a Decision Tree Regressor Model
Master non-linear regression models! 🚀
In this tutorial, we are building and visualizing a Decision Tree Regressor using Python, pandas, numpy, and scikit-learn.Unlike a standard straight linear regression line, a decision tree splits numeric data into constant prediction intervals. Watch how we train the model, use np.linspace to plot its unique step-like prediction line, and test how it forecasts a brand-new data point at $x = 11$!
📊 Elements Plotted in the Video Graph:
Black Scattered Dots (Date points): The original historical dataset coordinate plots.
Orange Stair Line (Decision tree regression): The predictive boundary steps calculated by the decision tree splits.
Red Target Dot (prediction for x=11): A live prediction test showcasing how the model outputs values for coordinates outside the training interval.
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#MachineLearning #Python #DataScience #DecisionTree #Regressor #Matplotlib #ScikitLearn #MYGCODING
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