5 a] Explain the fundamental differences between linear regression and logistic regression. the fundamental differences between Linear Regression and Logistic Regression: Aspect Linear Regression Logistic Regression Type of Problem Regression…
2.c) What is big data? Explain in detail 5 elements of bigdata. Answer: BIG Data BIG is a moving target – When the size of the data becomes a challenge,…
7.C] Explain the Servlet life cycle Answer:- The web container maintains the life cycle of a servlet instance.
6 b] Explain Principal Component Analysis. Principal Component Analysis (PCA) is a dimensionality reduction technique used to simplify a dataset while retaining most of the important information. PCA transforms the…
6 a] Explain Random Forest Classifier. The Random Forest Classifier is an ensemble machine learning algorithm that builds multiple decision trees and combines their predictions to produce a more accurate…
5.B] Write a note on:i) String comparisonii) String searching Answer:- String Comparison and Searching in Java i) String Comparison String comparison in Java involves checking whether two strings are identical…
2.a) Explain with neat diagram the current Landscape of data science process. Answer: The Current Landscape:
5 b] Define Feature Extraction. Explain different categories of information. Feature Extraction is the process of transforming raw data into a set of measurable, informative variables called features, which can…
5 a] Explain feature selection algorithms and selection criterion. Feature Selection Algorithms and Selection Criteria Feature Selection Algorithms: 2. Wrapper Method: Selection Criterion: 2. p-values: 3. AIC (Akaike Information Criterion):…
1.c) Describe the process of fitting a model to a dataset in detail. Answer: Fitting a Model Causes of Overfitting:
