# Category «Tensorflow»

## How to calculate score in Machine Learning

In order to calculate score of different types of Algorithm we use following types of methods, few methods from SkLearn library are mentioned below.   Scoring Function Comment Classification ‘accuracy’ metrics.accuracy_score ‘average_precision’ metrics.average_precision_score ‘f1’ metrics.f1_score for binary targets ‘f1_micro’ metrics.f1_score micro-averaged ‘f1_macro’ metrics.f1_score macro-averaged ‘f1_weighted’ metrics.f1_score weighted average ‘f1_samples’ metrics.f1_score by multilabel sample ‘neg_log_loss’ metrics.log_loss …

## Classes in Python

A class is a wrapping of data member and  member function inside a single unit. Lets take an example of a Interest class in which we have members, principal, rate and time. We have member function as SimpleIntrest. class Interest(): rate=3.5 def __init__(self,p,t): #Data Members self.principal=p self.rate=self.rate self.time=t self.si=self.principal*self.rate*self.time/100 pass #Memeber Function def SimpleIntrest(self): print(self.si) …

## Generalized Linear Models

Here general refers to the dependence on potentially more than one explanatory variable, v.s. the simple linear model : Some of the Generalized liner models are: 1-Ordinary Least Squares :Linear Regression fits a linear model with coefficients to minimize the residual sum of squares between the observed responses in the data set, and the responses …

## learning Model

5 Step Life-Cycle for Neural Network Models in Keras