Siraj Raval's 'Learn Python for Data science' playlist Video 1 https://youtu.be/T5pRlIbr6gg?list=PL2-dafEMk2A6QKz1mrk1uIGfHkC1zZ6UU
Note: I used a different and larger dataset available on internet for training and testing the models.
Find 3 more classifiers from the sci-kit learn documentation and add them to the code. Train them on the same dataset and compare their results. The following classifiers were chosen:
• Decision Tree Classifier
• Nearest Neighbour Classifier
• Random Forest Classifier
• Naive Bayes Classifier
just run
python classifier.py
• DecisionTreeClassifier Accuracy: 90.98%
• KNeighborsClassifier Accuracy: 87.27%
• RandomForestClassifier Accuracy: 90.72%
• GaussianNB Accuracy: 84.88%