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Recent questions tagged machine-learning
Home
Tag
machine-learning
+2
votes
Q: Which of the following option is used for machine learning on Hadoop?
asked
Jan 13
in
Hadoop
by
john ganales
(
14.1k
points)
hadoop
machine-learning
+1
vote
Q: We usually use feature normalization before using the Gaussian kernel in SVM.
asked
Jan 12
in
Machine Learning
by
john ganales
(
14.1k
points)
normalization
machine-learning
+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?
asked
Jan 12
in
Machine Learning
by
john ganales
(
14.1k
points)
variance
machine-learning
+1
vote
Q: Suppose you have trained an SVM with linear decision boundary after training SVM,
asked
Jan 12
in
Machine Learning
by
john ganales
(
14.1k
points)
machine-learning
+1
vote
Q: Which of the following can help to reduce overfitting in an SVM classifier?
asked
Jan 12
in
Machine Learning
by
john ganales
(
14.1k
points)
svm-classifier
machine-learning
+1
vote
Q: Which of the following are real world applications of the SVM?
asked
Jan 12
in
Machine Learning
by
john ganales
(
14.1k
points)
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?
asked
Jan 12
in
Machine Learning
by
john ganales
(
14.1k
points)
bias-variance
machine-learning
+1
vote
Q: The kernel trick
asked
Jan 12
in
Machine Learning
by
john ganales
(
14.1k
points)
kernel-trick
machine-learning
+1
vote
Q: The cost parameter in the SVM means:
asked
Jan 12
in
Machine Learning
by
john ganales
(
14.1k
points)
svm
machine-learning
+1
vote
Q: The firing rate of a neuron
asked
Jan 12
in
Machine Learning
by
john ganales
(
14.1k
points)
machine-learning
+1
vote
Q: Which of the following can only be used when training data are linearlyseparable?
asked
Jan 12
in
Machine Learning
by
john ganales
(
14.1k
points)
linearlyseparable
machine-learning
+1
vote
Q: A perceptron adds up all the weighted inputs it receives, and if it exceeds a certain value, it outputs a 1, otherwise it just outputs a 0.
asked
Jan 12
in
Machine Learning
by
john ganales
(
14.1k
points)
machine-learning
+1
vote
Q: What are support vectors?
asked
Jan 12
in
Machine Learning
by
john ganales
(
14.1k
points)
support-vectors
machine-learning
+1
vote
Q: What do you mean by a hard margin?
asked
Jan 12
in
Machine Learning
by
john ganales
(
14.1k
points)
hard-margin
machine-learning
0
votes
Q: Differentiate between Deep Learning and Machine Learning.
asked
Dec 13, 2022
in
Deep Learning
by
Robindeniel
(
20.8k
points)
deep-learning
machine-learning
+4
votes
Q: What characterize is hyperplance in geometrical model of machine learning?
asked
Dec 6, 2022
in
Machine Learning
by
sharadyadav1986
(
31.7k
points)
machine-learning
+4
votes
Q: Which of the following techniques would perform better for reducing dimensions of a data set?
asked
Dec 6, 2022
in
Machine Learning
by
sharadyadav1986
(
31.7k
points)
machine-learning
+4
votes
Q: A feature F1 can take certain value: A, B, C, D, E, & F and represents grade of students from a college. Here feature type is
asked
Dec 6, 2022
in
Machine Learning
by
sharadyadav1986
(
31.7k
points)
machine-learning
+4
votes
Q: Following is powerful distance metrics used by Geometric model
asked
Dec 5, 2022
in
Machine Learning
by
sharadyadav1986
(
31.7k
points)
matrix
machine-learning
+4
votes
Q: Which of the following is a good test dataset characteristic?
asked
Dec 5, 2022
in
Machine Learning
by
sharadyadav1986
(
31.7k
points)
machine-learning
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