ML-Unit2

The difference between the observed value and the mean value is called:

• residual

• outliers

When a data model is unable to capture the relationship between the input and output variables accurately, generating a high error rate on both the training set and unseen data it is said to be:

• Overfitted

• Underfitted

• Best-fitted

• loosely-fiited

Estimating future data outside your data range is termed as:

• Extrapolation

• Interpolation

Pick the correct statement:

• Regression algorithms are used to predict discrete values.

  Classification algorithms are used to predict/classify a continuous values.

• Both Regression and Classification algorithms are used to predict continuous values.

• Regression algorithms are used to predict continuous values.

  Classification algorithms are used to predict/classify a discrete values.

• Both Regression and Classification algorithms are used to predict discrete values.

Which of the following is not a Classification method?

• Logistic Regression

• Naive Bayes

• Linear Regression

• KNN

State True or False: The smaller the residual sum of squares, the better your model fits your data;

• TRUE

• FALSE

In which of the following Performance Metric, do we add 1 to both actual and predicted value?

• MSE

• RMSLE

• RMSE

• MAE

The process of predicting categorical variables where the output is restricted to two classes is:

• Binary Classification

• Multiclass Classification

In One-vs-One method, the model will:

• Fit one binary classification model for each class vs. all other classes.

• Fit one binary classification model for each pair of classes.

• Both A and B

• Neither A nor B

_____ expresses the proportion of units our model says are Positive and they are actually Positive.

• Accuracy

• Specificity

• Recall

• Precision