math · Uncategorized

Lagrange Multiplier With Equality Constraints

  Stationary Point Definition of stationary point from wikipedia : In mathematics, particularly in calculus, a stationary point or critical point of a differentiable function of one variable is a point on the graph of the function where the function's derivative is zero. Informally, it is a point where the function "stops" increasing or decreasing… Continue reading Lagrange Multiplier With Equality Constraints

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Classification – One vs Rest and One vs One

  In the blog post on Cost Function And Hypothesis for LR we noted that LR (Logistic Regression) inherently models binary classification. Here we will describe two approaches used to extend it for multiclass classification. One vs Rest approach takes one class as positive and rest all as negative and trains the classifier. So for the data having… Continue reading Classification – One vs Rest and One vs One

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Cross-validation in sklearn

When should we split data in three parts (namely train, cv, test) or just two parts (train and test)? Ref : http://stats.stackexchange.com/questions/19048/what-is-the-difference-between-test-set-and-validation-set When you apply the model to real world data, you want a number which says how much confident you are, say 80%. What if you divide data in two parts? Train, Test In case… Continue reading Cross-validation in sklearn

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Dimentionality Reduciton – Correlation

So sometimes we get many many feature variable, say 50 for now. (Can be much more in practice). And model is always good with small features unless they are necessary. Technically it is knows as dimensionality reduction and keeps model from over-fitting. Here is the great blog about this. It talks about correlation and mutual information.… Continue reading Dimentionality Reduciton – Correlation