Monday , June 17 2024
Breaking News

A Foundation Program in Data Science Quiz Answers – Grey Campus

  • linear, numeric
  • linear, binary
  • nonlinear, numeric
  • nonlinear, binary
  • PCA
  • Decision Tree
  • Linear Regression
  • Naive Bayesian
  • Least Square Error
  • Maximum Likelihood
  • Logarithmic Loss
  • Both A and B
  • The polynomial degree
  • Whether we learn the weights by matrix inversion or gradient descent
  • The use of a constant-term
  • None of the above
  • Mean of residuals is always zero
  • Mean of residuals is always less than zero
  • Mean of residuals is always greater than zero
  • There is no such rule for residuals.
  • Linear Regression with varying error terms
  • Linear Regression with constant error terms
  • Linear Regression with zero error terms
  • None of these
  • Scatter plot
  • Bar chart
  • Histograms
  • None of these
  • Ridge regression uses subset selection of features
  • Lasso regression uses subset selection of features
  • Both use subset selection of features
  • None of above
  • The relationship is symmetric between x and y in both.
  • The relationship is not symmetric between x and y in both.
  • The relationship is not symmetric between x and y in case of correlation but in case of regression it is symmetric.
  • The relationship is symmetric between x and y in case of correlation but in case of regression it is not symmetric.
  • Ridge regression
  • Lasso
  • Both Ridge and Lasso
  • None of both
  • The polynomial degree
  • Whether we learn the weights by matrix inversion or gradient descent
  • The use of a constant-term
  • None of the above
  • You will always have test error zero
  • You can not have test error zero
  • None of the above
  • Both A and B
  • Correlation coefficient = 0.9
  • The p-value for the null hypothesis Beta coefficient =0 is 0.0001
  • The t-statistic for the null hypothesis Beta coefficient=0 is 30
  • None of these
  • Random Forest
  • Extra Trees
  • Gradient Boosting
  • Decision Trees
  • 1 and 2
  • 2 and 3
  • 1 and 3
  • 1,2 and 3
  • Measure performance over training data
  • Measure performance over validation data
  • Both of these
  • None of these
  • Classifiers which form a tree with each attribute at one level.
  • Classifiers which perform series of condition checking with one attribute at a time.
  • Both the options given above.
  • None of the above
  • By pruning the longer rules
  • By creating new rules
  • Both By pruning the longer rules’ and ‘ By creating new rules’
  • None of the option
  • In pre-pruning a tree is ‘pruned’ by halting its construction early.
  • A pruning set of class labeled tuples is used to estimate cost complexity.
  • The best pruned tree is the one that minimizes the number of encoding bits.
  • All of the above
  • CART
  • ID3
  • Bayesian Classifier
  • Random Forest

About Clear My Certification

Check Also

ISRO

12th MOOC on “Overview of Space Exploration” by ISRO

Space Science and technology are exciting areas for scientists and researchers which has greatly impacted …

Leave a Reply

Your email address will not be published. Required fields are marked *