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Recent questions and answers in Machine Learning
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Questions
Machine Learning
0
votes
Which method is frequently used to prevent overfitting?
answered
Mar 16
in
Machine Learning
by
SakshiSharma
(
30.8k
points)
overfitting
machine
learning
+1
vote
What are the two methods used for the calibration in Supervised Learning?
answered
Mar 16
in
Machine Learning
by
SakshiSharma
(
30.8k
points)
supervised
learning
0
votes
What is a model selection in Machine Learning?
answered
Mar 16
in
Machine Learning
by
SakshiSharma
(
30.8k
points)
model-selection
0
votes
What is Inductive Logic Programming in Machine Learning?
answered
Mar 16
in
Machine Learning
by
SakshiSharma
(
30.8k
points)
logic
programming
machine
learning
0
votes
In what areas Pattern Recognition is used?
answered
Mar 16
in
Machine Learning
by
SakshiSharma
(
30.8k
points)
pattern
recognition
0
votes
What are the advantages of Naive Bayes?
answered
Mar 16
in
Machine Learning
by
SakshiSharma
(
30.8k
points)
naive
bayes
0
votes
What is classifier in machine learning?
answered
Mar 16
in
Machine Learning
by
SakshiSharma
(
30.8k
points)
machine
learning
0
votes
What is the difference between artificial learning and machine learning?
answered
Mar 16
in
Machine Learning
by
SakshiSharma
(
30.8k
points)
machine
learning
artificial
0
votes
What is algorithm independent machine learning?
answered
Mar 16
in
Machine Learning
by
SakshiSharma
(
30.8k
points)
algorithm
independent
machine
learning
0
votes
Explain what is the function of ‘Supervised Learning’?
answered
Mar 16
in
Machine Learning
by
SakshiSharma
(
30.8k
points)
supervised
learning
0
votes
Explain what is the function of ‘Unsupervised Learning’?
answered
Mar 16
in
Machine Learning
by
SakshiSharma
(
30.8k
points)
unsupervised
learning
0
votes
What is not Machine Learning?
answered
Mar 16
in
Machine Learning
by
SakshiSharma
(
30.8k
points)
machine
learning
0
votes
List down various approaches for machine learning?
answered
Mar 16
in
Machine Learning
by
SakshiSharma
(
30.8k
points)
machine
learning
0
votes
What is ‘Training set’ and ‘Test set’?
answered
Mar 16
in
Machine Learning
by
SakshiSharma
(
30.8k
points)
training
set
test
+1
vote
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
(
13.1k
points)
separable-dataset
+1
vote
Wrapper methods are hyper-parameter selection methods that
answered
Jan 12
in
Machine Learning
by
john ganales
(
13.1k
points)
machine-learining
+1
vote
We usually use feature normalization before using the Gaussian kernel in SVM.
answered
Jan 12
in
Machine Learning
by
john ganales
(
13.1k
points)
normalization
machine-learning
+1
vote
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
(
13.1k
points)
rbf-kernel
+1
vote
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
(
13.1k
points)
variance
machine-learning
+1
vote
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
(
13.1k
points)
binary-classifier
+1
vote
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
(
13.1k
points)
svm-kernel
+1
vote
Suppose you have trained an SVM with linear decision boundary after training SVM,
answered
Jan 12
in
Machine Learning
by
john ganales
(
13.1k
points)
machine-learning
+1
vote
Which of the following can help to reduce overfitting in an SVM classifier?
answered
Jan 12
in
Machine Learning
by
john ganales
(
13.1k
points)
svm-classifier
machine-learning
+1
vote
How can SVM be classified?
answered
Jan 12
in
Machine Learning
by
john ganales
(
13.1k
points)
svm-classification
+1
vote
Which of the following are real world applications of the SVM?
answered
Jan 12
in
Machine Learning
by
john ganales
(
13.1k
points)
svm-applications
machine-learning
+1
vote
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
(
13.1k
points)
bias-variance
machine-learning
+1
vote
The kernel trick
answered
Jan 12
in
Machine Learning
by
john ganales
(
13.1k
points)
kernel-trick
machine-learning
+1
vote
The cost parameter in the SVM means:
answered
Jan 12
in
Machine Learning
by
john ganales
(
13.1k
points)
svm
machine-learning
+1
vote
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
(
13.1k
points)
machine-leaning
logistic-regression
+1
vote
The firing rate of a neuron
answered
Jan 12
in
Machine Learning
by
john ganales
(
13.1k
points)
machine-learning
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