What is R-squared in machine learning? Let’s say a machine learning model gives the following output: [y1, y2, …, yn] And the actual output or the expected output is the following: [ya1, ya2, ya3, … yan] So, the error, in this case, is $latex e_{i}=y_{i}-y_{ai} \quad...
What is the Mean Absolute Error (MAE)? Let’s say we created a linear regression model. The expected output of the model is: [ya1, ya2, ya3, … yan] And the model gave the following output: [y1, y2, …, yn] The Mean Absolute Error (MAE) is the average of absolute error...
In our previous article, we discussed feature selection based on recursive elimination using sklearn. We can also select features based on model performance. For example, in the case of linear regression, we can select features and based on that calculate regression...
What is Recursive Feature Elimination (RFE)? In our previous articles, we discussed feature selection based on variance and correlation. These feature selection methods do not consider the output labels while selecting the features. As a result, these methods do not...
If two or more features in a dataset are strongly correlated, then we should select one of them. Selecting the right features for a machine learning model not only improves the performance of the model but also can reduce the training time of the algorithm. Whether...
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