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Regression in Python

How to Calculate Balanced Accuracy in Python Using sklearn

Balanced accuracy is a metric we can use to assess the performance of a classification model. It is calculated as: Balanced accuracy = (Sensitivity + Specificity)...

How to Plot Line of Best Fit in Python (With Examples)

You can use the following basic syntax to plot a line of best fit in Python: #find line of best fit a, b = np.polyfit(x, y,...

How to Perform One-Hot Encoding in Python

One-hot encoding is used to convert categorical variables into a format that can be readily used by machine learning algorithms. The basic idea of one-hot...

How to Calculate AUC (Area Under Curve) in Python

Logistic Regression is a statistical method that we use to fit a regression model when the response variable is binary. To assess how well a...

How to Calculate F1 Score in Python (Including Example)

When using classification models in machine learning, a common metric that we use to assess the quality of the model is the F1 Score. This...

How to Create a Confusion Matrix in Python

Logistic regression is a type of regression we can use when the response variable is binary. One common way to evaluate the quality of a...

How to Calculate BIC in Python

The Bayesian Information Criterion, often abbreviated BIC, is a metric that is used to compare the goodness of fit of different regression models. In practice,...

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