WorksheetsMachine Learning (Concept Learning)
Total questions: 25
Worksheet time: 17mins
_______ is the subset of objects or events defined over a larger set.
Entropy
Hierarchy
Concept
Learning
In hypothesis representation, what is the meaning of the symbol ' ? '
No value is acceptable
Any value is acceptable
Selected values are acceptable
None of the above
Positive examples of the data set are called as _________
hypothesis
Target concept
non members of the concept
members of the concept
The goal of concept learning is to find __________
hypothesis
training data set
testing data set
concept
Data set which has d binary features contains ______ concepts
22d
4d
42d
Which statements is/are true related to Find - s algorithm
considers both positive and negative samples
considers only positive samples
includes version space
No way to determine whether the hypothesis is consistent or not.
In Find-s algorithm, if the attribute value is matched with hypothesis value, what action has to be done?
No action. keep the value as it is.
replace it by ?
replace it by $
re phrase the entire hypothesis
________ is the simplest supervised machine learning algorithm used for classification based on how its neighbors are classified.
ANN
KNN
SVM
Clustering
How to choose the value of K in KNN?
Take the square root of the total data point available in the dataset.
Take the mean of the total data point available in the dataset.
Take the variance of the total data point available in the dataset.
Take the standard deviation of the total data point available in the dataset.
______ is the process of dividing datasets into different categories or groups by adding labels.
Regression
Clustering
Classification
K-means
______ is the graphical representation of all possible solutions to a decision.
K-Means
KNN
ANN
Decision Tree
______ is the classification Technique based on Baye's Theorem.
Decision Tree
SVM
Naive Bayes
Association
In Decision Tree, _____ is dividing the root node into different parts on the basis of some condition.
pruning
splitting
leaf node
parent node
_____ is a metrics used to measure impurity or randomness in data.
Sigmoid
Entropy
Step function
Categorical data
______ is a classification algorithm used to assign observations to a discrete set of classes.
Linear Regression
Multiple Linear Regression
Logistic Regression
Classification
The classification of spam mail and normal mail falls under _________ category.
Binary Logistic Regression
Multinomial Logistic Regression
Ordinal Logistic Regression
Linear Regression
____ is the fundamental unit of brain.
Lypcoses
Andrite
Neuron
Axon
In SVM, non linear problem can be solved by transforming data from _____ dimensional space into _____ dimensional space.
high, low
low, high
low, medium
medium, high
______ techniques combine individual models together to improve the stability and predictive power of the model.
SVM
ANN
Ensemble
KNN
Random Forest concepts are used to overcome ______
over fitting
complications in data
complexity in model
data noise
______ is a modeling error that occurs when a function is too closely fit to a limited set of data points.
under fitting
over fitting
linear fitting
logistic fitting
______ is the partition approach of grouping similar datas.
KNN
K-Means
ANN
HAC
The prior goal of unsupervised learning model is to determine the ________ .
classification task
regression task
accuracy of the classified labels
data patterns
Agglomerative clustering follows ________ .
top down approach.
bottom up approach
partitional clustering
model based clustering
Single linkage is the process of finding the distance between the _______ members of the two clusters.
farest
closest
average
mean
