MCQ IN COMPUTER SCIENCE & ENGINEERING

Previous
Next

COMPUTER SCIENCE AND ENGINEERING

MACHINE LEARNING

Question [CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
An emergency room in a hospital measures 17 variables (e.g. blood pressure, age etc.) of newly admitted patients. A decision has to be taken whether to put the patient in an intensive-care unit. Due to the high cost of ICU, those patients who may survive more a month are given higher priority. The problem is to predict high-risk patients and discriminate them from low-risk patients. What is the appropriate method of pattern identification (classification or clustering) used in machine learning in this problem?
A
Classification
B
Clustering
C
Either A or B
D
None of the above
Explanation: 

Detailed explanation-1: -The most commonly used Supervised Learning algorithms are decision tree, logistic regression, linear regression, support vector machine. The most commonly used Unsupervised Learning algorithms are k-means clustering, hierarchical clustering, and apriori algorithm.

Detailed explanation-2: -Classification is a data mining function that assigns items in a collection to target categories or classes. The goal of classification is to accurately predict the target class for each case in the data. For example, a classification model could be used to identify loan applicants as low, medium, or high credit risks.

Detailed explanation-3: -Examples of classification problems include: Given an example, classify if it is spam or not. Given a handwritten character, classify it as one of the known characters. Given recent user behavior, classify as churn or not.

Detailed explanation-4: -A decision tree is a largely used non-parametric effective machine learning modeling technique for regression and classification problems. To find solutions a decision tree makes sequential, hierarchical decision about the outcomes variable based on the predictor data.

There is 1 question to complete.
Previous
Next