Selecting machine learning algorithms

This section is the most important one. Here, we will try a couple of different ML algorithms in order to get an idea about which ML algorithm performs better. Also, we will perform a training accuracy comparison.

By this time, you will definitely know that this particular problem is considered a classification problem. The algorithms that we are going to choose are as follows (this selection is based on intuition):

  • K-Nearest Neighbor (KNN)
  • Logistic Regression
  • AdaBoost
  • GradientBoosting
  • RandomForest

Our first step is to generate the training data in a certain format. We are going to split the training dataset into a training and testing dataset. So, basically, we are preparing the input for our training. This is common ...

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