InterviewSolution

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This section includes InterviewSolutions, each offering curated multiple-choice questions to sharpen your knowledge and support exam preparation. Choose a topic below to get started.

1.	What are different types of Supervised learning
Answer» What are different types of Supervised learning Choose the correct option from below LIST (1)regression and CLASSIFICATION (2)Naive Bayes & classification (3)Segmentation and regression (4)Clustering and regression Answer:-(1)regression and classification

2.	Which technique implicitly defines the class of possible
Answer» Which technique implicitly defines the class of possible patterns by introducing a NOTION of similarity between data? Choose the correct option from below LIST (1)LINEAR Regression (2)Multi-Linear Regression (3)Hierarchical clustering (4)SVM (5)Kernel Answer:-(5)Kernel

3.	Which methodology works with clear margins of separation points?
Answer» Which methodology works with clear margins of SEPARATION POINTS? Choose the correct OPTION from below list (1)Linear REGRESSION (2)Logistic Regression (3)SUPPORT Vector Machine (4)Multi-Linear Regression Answer:-(3)Support Vector Machine

4.	Kernel methods can be used for supervised and unsupervised problems
Answer» Kernel METHODS can be used for supervised and UNSUPERVISED problems Choose the CORRECT answer from below list (1)FALSE (2)True Answer:-(2)True

5.	What is the benefit of Na ve Bayes ?
Answer» What is the benefit of Na ve BAYES ? CHOOSE the correct information from below list (1)can process faster with any data (2)Does not require any data (3)can handle any data VOLUME easily (4)REQUIRES LESS training data Answer:-(4)Requires less training data

6.	Which model helps SVM to implement the algorithm in high dimensional space?
Answer» Which model helps SVM to implement the ALGORITHM in high DIMENSIONAL space? CHOOSE the correct option from below list (1)Classification (2)Multi-Linear Regression (3)Kernel (4)Logistic Regression Answer-(3)Kernel

7.	Now Can you make quick guess where Decision tree will fall into _____
Answer» Now Can you make QUICK guess where Decision tree will fall into _____ CHOOSE the correct information from below LIST:- (1)Supervised Learning (2)Unsupervised Learning Answer:-(1)Supervised Learning

8.	For which one of these relationships could we use a regression analysis? Choose the correct one
Answer» For which one of these relationships could we use a regression analysis? Choose the CORRECT one (1)Relation between age and person is married (2)Relationship between Height & weight (both Quantitative) (3)Relationship between eye color (blue/black) and hair color (grey,blonde) (4)Relationship between being part of committee and NUMBER of eye operations Answer:-(2)Relationship between Height & weight (both Quantitative)

9.	Disadvantage of Neural network according to your purview is
Answer» Disadvantage of Neural network ACCORDING to your purview is Choose the correct option from below list (1)More nodes to be DEFINED (2)ITERATIONS should be defined (3)takes long TIME to be TRAINED Answer:-(3)takes long time to be trained

10.	Which type of the clustering could handle Big Data?
Answer» Which type of the CLUSTERING could HANDLE Big DATA? CHOOSE the correct OPTION from below list (1)K Means clustering (2)Hierarchical clustering Answer:-(1)K Means clustering

11.	Perceptron is _______________
Answer» Perceptron is _______________ Choose the CORRECT OPTION from below list (1)a single layer feed-forward NEURAL network (2)a DOUBLE layer auto-associative neural network (3)an auto-associative neural network Answer:-(1)a single layer feed-forward neural network

12.	The main difficulty with using a regression line to analyze these data is _________________
Answer» The MAIN difficulty with using a REGRESSION line to ANALYZE these data is _________________ Choose the correct option from below list (1)Response variable is not appropriate (2)merging of groups (3)presence of 1 or more OUTLIERS (4)Curvilinear data Answer:-(3)presence of 1 or more outliers

13.	What are the advantages of neural networks
Answer» What are the ADVANTAGES of neural networks (i) ability to learn by example (ii) fault tolerant (iii) SUITED for real time operation DUE to their high computational rates (1)(ii) and (iii) are true (2)(i) and (ii) are true (3)(i) and (iii) are true (4)All the options are correct Answer:-(4)All the options are correct

14.	In a scenario, where the statistical model describes random
Answer» In a scenario, where the statistical MODEL describes random error or noise instead of underlying relationship, what happens Choose the correct option from below LIST (1)TRANSDUCTION (2)Probabilistic NETWORKS (3)Overfitting (4)Underfitting Answer:-(3)Overfitting

15.	Effect of outlier on the correlation coefficient ______________
Answer» Effect of outlier on the correlation COEFFICIENT ______________ Choose the correct OPTION from below list (1)no effect on a correlation coefficient (2)decrease the correlation coefficient (3)An outlier might either decrease or INCREASE a correlation coefficient, depending on where it is in relation to the other points (4)increase a correlation coefficient Answer:-(3)An outlier might either decrease or increase a correlation coefficient, depending on where it is in relation to the other points

16.	Which of the following is not example of Clustering?
Answer» Which of the following is not example of Clustering? CHOOSE the correct option from below list (1)Image SEGMENTATION (2)Anomaly detection (3)Market segmentation (4)RECOMMENDATION engines (5)RFM ANALYSIS Answer:-(5)RFM Analysis

17.	Does Logistic regression check for the linear relationship between dependent and independent variables ?
Answer» Does Logistic regression check for the LINEAR relationship between dependent and INDEPENDENT VARIABLES ? (1)FALSE (2)True Answer:-(1)False

18.	One has to run through ALL the samples in your training set to
Answer» One has to RUN through ALL the samples in your TRAINING SET to do a single update for a parameter in a particular iteration. This is applicable for Choose the correct OPTION from below list (1)Neural Networks (2)Anomaly detection (3)Gradient Descent (4)STOCHASTIC gradient descent Answer:-(3)Gradient Descent