Building the revised approach

In this section, we will implement the various ML algorithms, check their precision score, and monitor their learning curve. There is a total of six ML algorithms that will be used to identify which one is the best suited for our application.

Implementing the revised approach

In this section, we will be implementing logistic regression, K-nearest neighbor, decision tree, random forest, Adaboost, and gradient descent. In order to implement this, we will be using the helper class that we built earlier. You can take a look at the code snippet given in the following screenshot:

Implementing the revised approach

Figure 3.68: Code snippet for performing training ...

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