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  1. 1.2. Linear and Quadratic Discriminant Analysis...

    X_k^tX_k = \frac{1}{n - 1} V S^2 V^t\) where \(V\) comes from the SVD...(centered) matrix: \(X_k = U S V^t\) . It turns out that we can...
    scikit-learn.org/stable/modules/lda_qda.html
    Fri Apr 26 16:41:50 UTC 2024
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  2. sklearn.base.RegressorMixin — scikit-learn 1.4....

    is defined as \((1 - \frac{u}{v})\) , where \(u\) is the residual...((y_true - y_pred)** 2).sum() and \(v\) is the total sum of squares...
    scikit-learn.org/stable/modules/generated/sklearn.base.RegressorMixin.html
    Fri Apr 26 16:41:48 UTC 2024
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  3. sklearn.compose.TransformedTargetRegressor — sc...

    is defined as \((1 - \frac{u}{v})\) , where \(u\) is the residual...((y_true - y_pred)** 2).sum() and \(v\) is the total sum of squares...
    scikit-learn.org/stable/modules/generated/sklearn.compose.TransformedTargetRegressor.html
    Fri Apr 26 16:41:50 UTC 2024
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  4. 2.5. Decomposing signals in components (matrix ...

    V^*) = \underset{U, V}{\operatorname{arg\,min\,}}...we multiply it with \(V_k\) : \[X' = X V_k\] Note Most treatments...
    scikit-learn.org/stable/modules/decomposition.html
    Fri Apr 26 16:41:50 UTC 2024
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  5. Slashdot: News for nerds, stuff that matters

    designing chips based on the RISC-V architecture, which is an open...pay a license fee to Arm. "RISC-V doesn't have a (large) software...
    slashdot.org/
    Fri Apr 26 01:18:16 UTC 2024
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  6. About us — scikit-learn 1.4.2 documentation

    V . and Thirion , B . and Grisel...and Weiss , R . and Dubourg , V . and Vanderplas , J . and Passos...
    scikit-learn.org/stable/about.html
    Fri Apr 26 16:41:50 UTC 2024
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  7. sklearn.linear_model.QuantileRegressor — scikit...

    is defined as \((1 - \frac{u}{v})\) , where \(u\) is the residual...((y_true - y_pred)** 2).sum() and \(v\) is the total sum of squares...
    scikit-learn.org/stable/modules/generated/sklearn.linear_model.QuantileRegressor.html
    Fri Apr 26 16:41:50 UTC 2024
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  8. sklearn.linear_model.LinearRegression — scikit-...

    is defined as \((1 - \frac{u}{v})\) , where \(u\) is the residual...((y_true - y_pred)** 2).sum() and \(v\) is the total sum of squares...
    scikit-learn.org/stable/modules/generated/sklearn.linear_model.LinearRegression.html
    Fri Apr 26 16:41:50 UTC 2024
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  9. sklearn.multioutput.MultiOutputRegressor — scik...

    is defined as \((1 - \frac{u}{v})\) , where \(u\) is the residual...((y_true - y_pred)** 2).sum() and \(v\) is the total sum of squares...
    scikit-learn.org/stable/modules/generated/sklearn.multioutput.MultiOutputRegressor.html
    Fri Apr 26 16:41:50 UTC 2024
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  10. sklearn.svm.NuSVR — scikit-learn 1.4.2 document...

    is defined as \((1 - \frac{u}{v})\) , where \(u\) is the residual...((y_true - y_pred)** 2).sum() and \(v\) is the total sum of squares...
    scikit-learn.org/stable/modules/generated/sklearn.svm.NuSVR.html
    Fri Apr 26 16:41:48 UTC 2024
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