ML Algorithms for Beginners

#ML-Algorithms-for-Beginners

This image provides a high level overview on the different types of ML algorithms and how to select them

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Import Packages

#Import-Packages
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Get the labels and assign it to a labels variable

#Get-the-labels-and-assign-it-to-a-labels-variable
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Split the dataset into training and testing set

#Split-the-dataset-into-training-and-testing-set
  • X is a matrix, hence it is represented in uppercase
  • y is a vector, hence it is represented in lowercase
  • test_size is 20%, that means train_size is 80%
  • random state is for reproducibility

Initialize a TFidfVectorizer, fit and transform the train set and transform the test set

#Initialize-a-TFidfVectorizer,-fit-and-transform-the-train-set-and-transform-the-test-set

Initialize a PassiveAggressiveClassifier and Predict on the test set

#Initialize-a-PassiveAggressiveClassifier-and-Predict-on-the-test-set
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Print the Classification Report, Confusion Matrix and Accuracy

#Print-the-Classification-Report,-Confusion-Matrix-and-Accuracy
  • TP: 589
  • TN: 587
  • FP: 49
  • FN: 43