Logistic Regression, Random Forest, Neural Networks, Image Processing, Computer Vision.
%pipeline2.score(X_test_std, y_test)) PCA_LDA_Random(df) #Test Accuracy: RF after PCA 0.492 It is worth noting that the Random Forest Regression model tends to produce lower prediction results compared to other models. This is due to its tree-based decision process, which, despite the introduction