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