Machine Learning

The given figure represents to_______ method Stratification Transfer Learning None of the mentioned Ada-boost

Question 2 "Given a classifier Cand a set of feature F,_________searches in the space of subsets of F, using cross validation to compare the performance of the trained classifier Con each tested subset." None of the mentioned An embeded method A filter method A wrapper method

Question 3 The problem with class imbalances is that standard learners are often biased towards the minority class. TRUE FALSE

Question 4 The bootstrap method use sampling__________ to form the training set. Without replacement With replacement Half with replacement and half without replacement

Question 5 Calculate the False Negative from the given table. None of the mentioned 1 4 2

Question 6 SMOTE is used for ________________________ (A)Balanced Data (B)setFeature Selection (C)None of the mentioned (D)Feature Extraction

Question 7 _____________True Positive/True Positive + False Negative) F Measure Precision Recall None of the mentioned

Question 8 The objective of_________ is to discover or to reduce the dimensionality of the data set and to remove the collinearity among the data, Principal Component Analysis SMOTE K-fold cross validation None of the mentioned

How many number of association rules are possible according to this basket data? 602 1932 64 127

Question 10 __________method select features based on statistical properties. None of the mentioned An embeded method A filter method A wrapper method

Question 11 SMOTE stands for___________ Synthetic Minority Oversampling Technique Synthetic Majority Overgeneralization Technique None of the mentioned Synthetic Majority Oversampling Technique

Question 12 Homgeneous classifers use______________ Same Algorithm over diversified Data sets Same Algorithm over same data Different learning algorithms over the same data Different learning algorithms over the diversified data

The given figure represents to_________________method None of the mentioned Bagging Ada-boost Stratification

Question 14 Precision and Recall are used to evaluate the_____ model None of the mentioned Regression model Classification model

Question 15 _______________might hurt performance on noisy datasets. Bagging None of the mentioned Boosting

Question 16 Stratification makes sure that each class is represented with approximately equal proportions in both subsets. TRUE FALSE

Question 17 "In PCA Elgen Vectors show the________________ of axes of a fitted ellipsoid and Eigen Values show the______________ of the corresponding axis." None of the mentioned "Direction, Significance" "Significance, Direction"

How many numbers of item sets are possible according to this basket data? 63 64 128 127

Question 19 Bagging and Boosting are______________________ Homogeneous dassifiers Heterogeneous classifiers

Question 20 PGA is used for____________________

None of the mentioned Finding the validity of model Balanced Data set Feature Reduction

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