Hello friends in this post we are going to discuss about Machine Learning Axioms TCS Fresco Play Dumps | Machine Learning Axioms TCS Fresco Play Answers | Machine Learning Axioms TCS Answers | Machine Learning Axioms Objective type question answer
Q1.If you have a basket of different fruit varieties with some prior information on size, color, shape of each and every fruit . Which learning methodology is best applicable?
ANS – Supervised Learning
Q2.Do you think heuristic for rule learning and heuristics for decision trees are both same ?
False
Q3.What is the benefit of Naïve Bayes ?
ANS – Requires less training data
Q4.What is the advantage of using an iterative algorithm like gradient descent ? (select the best)
ANS – For Nonlinear regression problems, there is no closed form solution
Q5.For which one of these relationships could we use a regression analysis? Choose the correct one
ANS – Relationship between Height & weight (both Quantitative)
Q6.Does Logistic regression check for the linear relationship between dependent and independent variables ?
False
Q7.Which helps SVM to implement the algorithm in high dimensional space?
ANS – Kernel
Q8.Kernel methods can be used for supervised and unsupervised problems
True
Q9.Perceptron is _______
ANS – a single layer feed-forward neural network
Q10.While running the same algorithm multiple times, which algorithm produces same results?
ANS – Hierarchical clustering
Q11.SVM will not perform well with large data set because (select the best answer)
ANS – training time is high
Q12.In a scenario, where the statistical model describes random error or noise instead of underlying relationship, what happens
ANS – Overfitting
Q13.Consider a regression equation, Now which of the following could not be answered by regression?
ANS – Estimate whether the association is linear or non-linear
Q14.Now Can you make quick guess where Decision tree will fall into ______
ANS – Supervised Learning
Q15.The main difficulty with using a regression line to analyze these data is _____
ANS – presence of 1 or more outliers
Q16.For which one of these relationships could we use a regression analysis? Chose the correct one
ANS – Relationship between Height & weight (both Quantitative)
Q17.The correlation between two variables is given by r = 0.0. . This means
ANS – The best straight line through the data is horizontal.
Q18.Most famous technique used in Text mining is
ANS – Naive Bayes
Q19.Disadvantage of Neural network according to your purview is
ANS – takes long time to be trained
Q20.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
ANS – Gradient Descent
Q21.Which type of the clustering could handle Big Data?
ANS – K Means clustering
Q22.Effect of outlier on the correlation coefficient __
ANS – An outlier might either decrease or increase a correlation coefficient, depending on where it is in relation to the other points — Correct
Q23.If the outcome is continuous, which model to be applied?
ANS – Multi-Linear Regression
Q24.SVM uses which method for pattern analysis in High dimensional space?
ANS – Kernel
Q25.Correlation and regression are concerned with the relationship between _
ANS – 2 quantitative variables
Q26.Which model helps SVM to implement the algorithm in high dimensional space?
ANS – Kernel
Q27.In Kernel trick method, We do not need the coordinates of the data in the feature space
True
Q28.What are different types of Supervised learning
ANS – regression and classification
Q29.Which methodology works with clear margins of separation points?
ANS – Support Vector Machine
Q30.Which of the learning methodology applies conditional probability of all the variables with respective the dependent variable?
ANS – Supervised Learning
Q31.The main problem with using single regression line
ANS – presence of 1 or more outliers
Q32.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
ANS – All the options are correct
Q33.Which clustering technique requires prior knowledge of the number of clusters required?
ANS – K Means clustering
Q34.Which of them, best represents the property of Kernel?
ANS – Modularity
Q35.The model in which one estimates the probability that the outcome variable assumes a certain value, rather than estimating the value itself.
ANS – Logistic Regression
Q36.If the outcome is binary(0/1), which model to be applied?
ANS – Logistic Regression
Q37.SVM will not perform well with data with more noise because (select the best answer)
ANS – target classes could overlap
Q38.The standard approach to supervised learning is to split the set of example into the training set and the test
True