MACHINE LEARNING
106403Module 4: Clustering, K-means, K-medoids, Density-based Hierarchical, Spectral .
Q1b. (b) A Machine Learning technique that helps in detecting the outliers in data is called as: - (i) Clustering . (ii) Classification (iii) Anomaly Detection (iv) All of the above20232m
Module 4: Clustering, K-means, K-medoids, Density-based Hierarchical, Spectral .
View this question on its own page →(b) A Machine Learning technique that helps in detecting the outliers in data is called as:
- (i) Clustering .
(ii) Classification
(iii) Anomaly Detection
(iv) All of the above
- (i) Clustering .
Q1i. A hypothesis which defines the population distribution is called .... (i) Null Hypothesis . (ii) Positive Hypothesis (iii) Negative Hypothesis (iv) Alternative Hypothesis20232m
Module 4: Clustering, K-means, K-medoids, Density-based Hierarchical, Spectral .
View this question on its own page →A hypothesis which defines the population distribution is called ....
(i) Null Hypothesis .
(ii) Positive Hypothesis
(iii) Negative Hypothesis
(iv) Alternative HypothesisQ1i. What is the minimum number of variables/features required to perform clustering? (i) 0 (ii) 1 (iii) 2 (iv) 320222m
Module 4: Clustering, K-means, K-medoids, Density-based Hierarchical, Spectral .
View this question on its own page →What is the minimum number of variables/features required to perform clustering?
(i) 0
(ii) 1
(iii) 2
(iv) 3Q8a. What is the difference between K-means and K-medoid algorithm? Explain density-based hierarchical clustering.20227m
Module 4: Clustering, K-means, K-medoids, Density-based Hierarchical, Spectral .
View this question on its own page →What is the difference between K-means and K-medoid algorithm? Explain density-based hierarchical clustering.
Q8b. What is the difference between K-NN and K-means clustering algorithms?20237m
Module 4: Clustering, K-means, K-medoids, Density-based Hierarchical, Spectral .
View this question on its own page →What is the difference between K-NN and K-means clustering algorithms?