LOGISTIC REGRESSION IN PYTHON QUIZ DESCRIPTION Total Questions −30 00 Max Time − 15:00 How many types are available in machine learning? 2 3 4 5 What are the three types of Machine Learning? Supervised Learning Unsupervised Learning Reinforcement Learning All of the above What is the way to ensemble multiple classifications or regression? Bagging Blending Boosting Stacking Which methods are used for the calibration in Supervised Learning? Platt Calibration Isotonic Regression Both Platt Calibration & Isotonic Regression None of the above Common classes of problems in machine learning is .............. Clustering Regression Classification All of the above .................. algorithms enable the computers to learn from data, and even improve themselves, without being explicitly programmed. Deep Learning Machine Learning Artificial Intelligence None of the above Missing data items are ........................ with Bayes classifier. Ignored Treated as equal compares Treated as unequal compares. Replaced with a default value. The average positive difference between computed and desired outcome values Mean positive error Mean absolute error Mean squared error Root mean squared error Regression discovers causal relationships. True False Choose the incorrect numerical functions in the various function representation of machine learning. Case-based Neural Network Linear regression All of true Machine Learning has various function representation, which of the following is not function of symbolic? Decision Trees Rules in propotional Logic Rules in first-order predicate logic Hidden-Markov Models (HMM) Machine learning is a subset of ................ Deep Learning Artificial Intelligence Data Learining None of the above Identify which is not machine learning disciplines? Physiscs Information theory Nuero Statistics None of the above What is the most common issue when using Machine Learning? Poor Data Quality Lack of skilled resources Inadequate Infrastructure None of the above Which supervised learning technique can process both numeric and categorical input attributes? Bayes classifier Linear regression Ogistic regression None of the above How can you handle missing or corrupted data in a dataset? Drop missing rows or columns Assign a unique category to missing values Replace missing values with mean/median/mode All of the above What is the full form of PAC? Probably Approx Cost Probably Approximate Correct Probability Approx Communication None of the above If machine learning model output involves target variable then that model is called as predictive model. True False What is the most significant phase in a genetic algorithm? Selection Mutation Crossover Fitness function Which of the following is not numerical functions in the various function representation of Machine Learning? Case-based Neural Network Linear Regression Support Vector Machines Which of the following statement is true about prediction problems? The output attribute must be numeric. The output attribute must be categorical The resultant model is designed to determine future outcomes The resultant model is designed to classify current behavior. What is called the application of machine learning methods to large databases? Data mining Internet of things Artificial intelligence None of the above ............ is a widely used and effective machine learning algorithm based on the idea of bagging. Regression Classification Decision Tree Random Forest Regression trees are often used to model which data? Linear Nonlinear Categorical None of the above A Machine Learning technique that helps in detecting the outliers in data. Clustering Classification Anamoly Detection All of the above Which of the folloiwng clustering algorithm merges and splits nodes to help modify nonoptimal partitions? K-Means clustering Conceptual clustering Agglomerative clustering All of the above ............. is the approach of basic algorithm for decision tree induction. Greedy Top Down Procedural Step by Step What is machine learning? The selective acquisition of knowledge through the use of manual programs The selective acquisition of knowledge through the use of computer programs The autonomous acquisition of knowledge through the use of manual programs The autonomous acquisition of knowledge through the use of computer programs The Bayes rule can be used in ................ Solving queries Increasing complexity Decreasing complexity Answering probabilistic query What is the disadvantage of decision trees? Factor analysis Decision trees are robust to outliers Decision trees are prone to be overfit All of the above Previous Next Total Question16 Wrong Answer13 Right Answer13
