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Top 100+ questions and answers in Machine Learning
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Machine Learning
0
votes
Q: Which method is frequently used to prevent overfitting?
answered
Mar 16
in
Machine Learning
by
SakshiSharma
overfitting
machine
learning
0
votes
Q: What are the two methods used for the calibration in Supervised Learning?
answered
Mar 16
in
Machine Learning
by
SakshiSharma
supervised
learning
0
votes
Q: What is a model selection in Machine Learning?
answered
Mar 16
in
Machine Learning
by
SakshiSharma
model-selection
0
votes
Q: What is Inductive Logic Programming in Machine Learning?
answered
Mar 16
in
Machine Learning
by
SakshiSharma
logic
programming
machine
learning
0
votes
Q: In what areas Pattern Recognition is used?
answered
Mar 16
in
Machine Learning
by
SakshiSharma
pattern
recognition
0
votes
Q: What are the advantages of Naive Bayes?
answered
Mar 16
in
Machine Learning
by
SakshiSharma
naive
bayes
0
votes
Q: What is classifier in machine learning?
answered
Mar 16
in
Machine Learning
by
SakshiSharma
machine
learning
0
votes
Q: What is the difference between artificial learning and machine learning?
answered
Mar 16
in
Machine Learning
by
SakshiSharma
machine
learning
artificial
0
votes
Q: What is algorithm independent machine learning?
answered
Mar 16
in
Machine Learning
by
SakshiSharma
algorithm
independent
machine
learning
0
votes
Q: Explain what is the function of ‘Supervised Learning’?
answered
Mar 16
in
Machine Learning
by
SakshiSharma
supervised
learning
0
votes
Q: Explain what is the function of ‘Unsupervised Learning’?
answered
Mar 16
in
Machine Learning
by
SakshiSharma
unsupervised
learning
0
votes
Q: What is not Machine Learning?
answered
Mar 16
in
Machine Learning
by
SakshiSharma
machine
learning
0
votes
Q: List down various approaches for machine learning?
answered
Mar 16
in
Machine Learning
by
SakshiSharma
machine
learning
0
votes
Q: What is ‘Training set’ and ‘Test set’?
answered
Mar 16
in
Machine Learning
by
SakshiSharma
training
set
test
+1
vote
Q: Which of the following methods can not achieve zero training error on any linearly separable dataset?
answered
Jan 12
in
Machine Learning
by
john ganales
separable-dataset
+1
vote
Q: Wrapper methods are hyper-parameter selection methods that
answered
Jan 12
in
Machine Learning
by
john ganales
machine-learining
+1
vote
Q: We usually use feature normalization before using the Gaussian kernel in SVM.
answered
Jan 12
in
Machine Learning
by
john ganales
normalization
machine-learning
+1
vote
Q: Suppose you are using RBF kernel in SVM with high Gamma value. What does this signify?
answered
Jan 12
in
Machine Learning
by
john ganales
rbf-kernel
+1
vote
Q: Suppose your model is demonstrating high variance across the different training sets. Which of the following is NOT valid way to try and reduce the variance?
answered
Jan 12
in
Machine Learning
by
john ganales
variance
machine-learning
+1
vote
Q: You trained a binary classifier model which gives very high accuracy on the training data, but much lower accuracy on validation data. Which is false.
answered
Jan 12
in
Machine Learning
by
john ganales
binary-classifier
+1
vote
Q: What is/are true about kernel in SVM? 1. Kernel function map low dimensional data to high dimensional space 2. It’s a similarity function
answered
Jan 12
in
Machine Learning
by
john ganales
svm-kernel
+1
vote
Q: Suppose you have trained an SVM with linear decision boundary after training SVM,
answered
Jan 12
in
Machine Learning
by
john ganales
machine-learning
+1
vote
Q: Which of the following can help to reduce overfitting in an SVM classifier?
answered
Jan 12
in
Machine Learning
by
john ganales
svm-classifier
machine-learning
+1
vote
Q: How can SVM be classified?
answered
Jan 12
in
Machine Learning
by
john ganales
svm-classification
+1
vote
Q: Which of the following are real world applications of the SVM?
answered
Jan 12
in
Machine Learning
by
john ganales
svm-applications
machine-learning
+1
vote
Q: How does the bias-variance decomposition of a ridge regression estimator compare with that of ordinary least squares regression?
answered
Jan 12
in
Machine Learning
by
john ganales
bias-variance
machine-learning
+1
vote
Q: The kernel trick
answered
Jan 12
in
Machine Learning
by
john ganales
kernel-trick
machine-learning
+1
vote
Q: The cost parameter in the SVM means:
answered
Jan 12
in
Machine Learning
by
john ganales
svm
machine-learning
+1
vote
Q: Which of the following evaluation metrics can not be applied in case of logistic regression output to compare with target?
answered
Jan 12
in
Machine Learning
by
john ganales
machine-leaning
logistic-regression
+1
vote
Q: The firing rate of a neuron
answered
Jan 12
in
Machine Learning
by
john ganales
machine-learning
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