python-machine-learning-book - The "Python Machine Learning" book code repository and info resource
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python-machine-learning-book - The "Python Machine Learning" book code repository and info resource

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python-machine-learning-book - The "Python Machine Learning" book code repository and info resource
1. Mean centering does not affect the covariance matrix
[..] Even centering only one variable, e.g., x wouldn’t affect the covariance [..]
2. Scaling of variables does affect the covariance matrix
Say $A$ and $B$ are symmetric, positive definite matrices. I've proved that $\det(A+B) \ge \det(A) + \det(B)$ in the case that $A$ and $B$ are two dimensional. Is this true in general for $n$-

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Let's get our feet wet by thinking in terms of vectors and spaces.
This lesson shows how to calculate the determinant of any square matrix. Introduces notation for matrix determinants. Includes problems with solutions.
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I have obtained the confusion matrix. I want to display it in the window organized in a table as follows:
CONFUSION MATRIX:
Hmm, a wild guess maybe but I see where that name comes from :p
So, in such a matrix how can I picture coefficients and variables being allocated??
If for example I wnated to write as a matrix the results of bloodwork test for 5 patients/samples.
What would the piture actually be of that matrix?
Και ποια θα ήταν η φυσική σημασία της λύσης του συστήματος?
Μία πρόβλεψη??
The scalar triple product (also called the mixed product, box product, or triple scalar product) is defined as the dot product of one of the vectors with the cross product of the other two.
The scalar triple product (also called the mixed product, box product, or triple scalar product) is defined as the dot product of one of the vectors with the cross product of the other two.