Placeholder_text correction and adding hints#63
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YaroslavMayorov wants to merge 2 commits intomasterfrom
Open
Placeholder_text correction and adding hints#63YaroslavMayorov wants to merge 2 commits intomasterfrom
YaroslavMayorov wants to merge 2 commits intomasterfrom
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@stephen-hero Please read the comments in Pima Indians Diabets and Linear Classifier/Read data/task.py. |
stephen-hero
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Mar 13, 2026
| # with a unit standard deviation. This means that the mean | ||
| # and standard deviation of the standard scores are 0 and 1, respectively. | ||
| # This procedure is recommended for data that follows a normal distribution. | ||
| # Normalize features: for each column subtract its mean |
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Standardize features: subtract the mean
| # and standard deviation of the standard scores are 0 and 1, respectively. | ||
| # This procedure is recommended for data that follows a normal distribution. | ||
| # Normalize features: for each column subtract its mean | ||
| # and divide by its standard deviation. |
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and divide by the standard deviation for each column.
| # and divide by its standard deviation. | ||
| X = (X - X.mean(axis=0)) / X.std(axis=0) | ||
| # A column of -1s is prepended to the left of the X array. | ||
| # Add a column of -1s to the left of X. |
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Prepend a column of -1s to X.
| # calculations later on. | ||
| X = np.concatenate((-np.ones(len(X)).reshape(-1, 1), X), axis=1) | ||
| # y is standardized: centered around 0 with a standard deviation of 1. | ||
| # Convert labels from {0,1} to {1,-1}. |
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Map labels from {0,1} to {1,-1}.
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