Start learning 50% faster. Sign in now
K-Means Clustering is a technique most suitable for identifying underlying patterns in high-dimensional data without the need for explicit labeling. It groups data into clusters based on similarity, where each cluster represents a pattern or structure in the data. K-Means is useful for exploratory data analysis to discover patterns or groupings within unlabelled data. Why Other Options are Wrong: a) Principal Component Analysis (PCA) reduces dimensionality but does not identify patterns or groupings. b) Linear Regression is a supervised learning technique used for predicting continuous values rather than identifying patterns in unlabelled data. d) Decision Trees are used for classification or regression tasks and require labelled data. e) Naive Bayes Classifier is a classification algorithm that also requires labelled data and does not identify patterns in unlabelled datasets.
Dhirendra Ojha was recently appointed as the Director General of which organization?
When did India's presidency of the G20 forum begin?
What is the goal for Gross Enrolment Ratio (GER) in higher education according to NEP 2020?
In which country was the 'RIMPAC Exercise' held, in which the Indian Navy recently participated?
Recently, the cabinet of which state has approved ‘Mob Lynching Victim Muacha Scheme’?
Who inaugurated the 'Khadi Mahotsav' organized by Khadi and Village Industries in Mumbai?
The 4th edition of the AIM-ICDK Water Innovation Challenge was successfully concluded in November 2024. Which country collaborated with India for this ...
Who is the first player from Assam to make it to the Indian women's team?
What new international recognition did Thiruvananthapuram International Airport achieve in May 2024?
In June 2024, how much was invested by the Ahmedabad Municipal School Board for the construction of 30 smart schools under the New Education Policy (NEP...