sklearn

[Fixed] Unknown label type: ‘continuous’ in sklearn LogisticRegression

Error, Python, sklearn / By

Summary: Use SKLearn’s LogisticRegression Model for classification problems only. The Y variable is a category (e.g., binary [0,1]), not continuous (e.g. float numbers 3.4, 7.9). If the Y variable is non-categorical (i.e., continuous), the potential fixes are as follows. Re-examine the data. Try to encode the continuous Y variable into categories (e.g., use SKLearn’s LabelEncoder preprocessor). Re-examine …

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Sklearn fit() vs transform() vs fit_transform() – What’s the Difference?

Artificial Intelligence, Data Science, Machine Learning, Python, sklearn / By

Scikit-learn has a library of transformers to preprocess a data set. These transformers clean, generate, reduce or expand the feature representation of the data set. These transformers provide the fit(), transform() and fit_transform() methods. The fit() method identifies and learns the model parameters from a training data set. For example, standard deviation and mean for …

Sklearn fit() vs transform() vs fit_transform() – What’s the Difference? Read More »

How To Plot SKLearn Confusion Matrix With Labels?

Artificial Intelligence, Data Science, Data Visualization, Machine Learning, Math, Matplotlib, Python, sklearn / By

Summary: The best way to plot a Confusion Matrix with labels, is to use the ConfusionMatrixDisplay object from the sklearn.metrics module. Another simple and elegant way is to use the seaborn.heatmap() function. Note: All the solutions provided below have been verified using Python 3.9.0b5. Problem Formulation Imagine the following lists of Actual and Predicted values …

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