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Machine Learning Notes | mlnotesConfig GoAgent for Vmware. Bias and Variance Tradeoff. Pyright 2012 - 2014 by hanfeng.
http://www.mlnotes.com/
Config GoAgent for Vmware. Bias and Variance Tradeoff. Pyright 2012 - 2014 by hanfeng.
http://www.mlnotes.com/
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Machine Learning Notes | mlnotes | mlnotes.com Reviews
https://mlnotes.com
Config GoAgent for Vmware. Bias and Variance Tradeoff. Pyright 2012 - 2014 by hanfeng.
mlnotes.com
Config GoAgent for Vmware | mlnotes
http://mlnotes.com/2014/02/02/vmware_proxy.html
Config GoAgent for Vmware. Pyright 2012 - 2014 by hanfeng.
Linear Programming | mlnotes
http://mlnotes.com/2013/06/16/lp.html
In a linear programming problem, we are given a set of variables, and we want to assign real values to them so as to. Satisfy a set of linear equations and/or linear inequalities involving these variables. Maximize or minimize a given linear objective function. Linear Programs can be solved by the simplex method, devised by George Dantzig. In 1947. Typically there are three steps:. Starts at a vertex. Repeatedly looks for an adjacent vertex of better objective value, and moves to it.
Principal Component Analysis(PCA) | mlnotes
http://mlnotes.com/2013/08/28/pca.html
Suppose $ $ X $ $ is a $ $ n times p $ $ matrix, where n is the number of objects and p is the number of features. $ $X$ $ is zero mean. X T X = nV $ $ $ V $ $ is the covariance matrix of $ $X$ $, and it's obvious that $ $V$ $ is a symmetric and positive-definite matrix. Begin{eqnarray*} vec{x} i - ( vec{x} i cdot vec{w}) vec{w} 2 &=& vec{x} i 2-2( vec{x} i cdot vec{w}) 2 ( vec{x} i cdot vec{w}) vec{w} 2 &=& vec{x} i 2 - ( vec{x} i cdot vec{w}) 2 end{eqnarray*} $. For all vectors, the residuals is:.
Knapsack | mlnotes
http://mlnotes.com/2013/06/15/knapsack.html
0-1 Knapsack without repetition. This is the most common case of Knapsack problem. It defines as:. Let $ $ U = {u 1, u 2, , u n }$ $ be a set of items to be packed in a knapsack of size $ $C$ $. For $ $ 1 leq j leq n$ $, let $ $ s j $ $ and $ $ v j $ $ be the size and value of the j-th item. Problem: We want to find a subset of $ $ S subseteq U $ $ such that. Sum {u j in S} v j $. Is maximized subject to the constraint. Sum {u j in S} s j leq C $. The result is V[n, C]. 0-1 Knapsack with repetition.
Knowledge Graph | mlnotes
http://mlnotes.com/2014/05/07/kg.html
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Machine Learning Notes | mlnotes
Config GoAgent for Vmware. Bias and Variance Tradeoff. Pyright 2012 - 2014 by hanfeng.
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