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Given m data records,

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Answer #1

The problem given as a linear regression problem (when we have continuous decision variable y(1), y(2) etc, and the relationship of the decision variable with the data is a linear one). Before describing the model I will tell you the assumptions taken for the linear regression:

• Linear relationship among target variable and input data
• Multivariate normality variables
• No or little multicollinearity among the features
• No auto-correlation among the output variables
• Homoscedasticity error

Now go through the image..for J(B), y (i) is the actual target output and y^(i) is the predicted by the linear regression.

fw each duh borint (x) we ure Covreskondin cueisim 0 for i dats poins anchan :一 rn Сее Min U) 2fbǐ Jui tial 2. Cradient Descent Aptanch,- Here we talus o (6)Bis un each s Wt&

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Answer 1

The problem given as a linear regression problem (when we have continuous decision variable y(1), y(2) etc, and the relationship of the decision variable with the data is a linear one). Before describing the model I will tell you the assumptions taken for the linear regression:

• Linear relationship among target variable and input data
• Multivariate normality variables
• No or little multicollinearity among the features
• No auto-correlation among the output variables
• Homoscedasticity error

Now go through the image..for J(B), y (i) is the actual target output and y^(i) is the predicted by the linear regression.

fw each duh borint (x) we ure Covreskondin cueisim 0 for i dats poins anchan :一 rn Сее Min U) 2fbǐ Jui tial 2. Cradient Descent Aptanch,- Here we talus o (6)Bis un each s Wt&