Top 350+ Solved Machine Learning (ML) MCQ Questions Answer
Q. According to____ , it’s a key success factor for the survival and evolution of all species.
a. Claude Shannon\s theory
b. Gini Index
c. Darwin’s theory
d. None of above
Q. What is ‘Training set’?
a. Training set is used to test the accuracy of the hypotheses generated by the learner.
b. A set of data is used to discover the potentially predictive relationship.
c. Both A & B
d. None of above
Q. Common deep learning applications include____
a. Image classification,Real-time visual tracking
b. Autonomous car driving,Logistic optimization
c. Bioinformatics,Speech recognition
d. All above
Q. Reinforcement learning is particularly efficient when______________.
a. the environment is not completely deterministic
b. it\s often very dynamic
c. it\s impossible to have a precise error measure
d. All above
Q. if there is only a discrete number of possible outcomes (called categories),the process becomes a______.
a. Regression
b. Classification.
c. Modelfree
d. Categories
Q. Which of the following are supervised learning applications
a. Spam detection,Pattern detection,Natural Language Processing
b. Image classification,Real-time visual tracking
c. Autonomous car driving,Logistic optimization
d. Bioinformatics,Speech recognition
Q. During the last few years, many ______ algorithms have been applied to deepneural networks to learn the best policy for playing Atari video games and to teach an agent how to associate the right action with an input representing the state.
a. Logical
b. Classical
c. Classification
d. None of above
Q. What is ‘Overfitting’ in Machine learning?
a. when a statistical model describes random error or noise instead of underlying relationship ‘overfitting’ occurs.
b. Robots are programed so that they can perform the task based on data they gather from sensors.
c. While involving the process of learning ‘overfitting’ occurs.
d. a set of data is used to discover the potentially predictive relationship
Q. What is ‘Test set’?
a. Test set is used to test the accuracy of the hypotheses generated by the learner.
b. It is a set of data is used to discover the potentially predictive relationship.
c. Both A & B
d. None of above
Q. ________is much more difficult because it's necessary to determine a supervised strategy to train a model for each feature and, finally, to predict their value
a. Removing the whole line
b. Creating sub-model to predict those features
c. Using an automatic strategy to input them according to the other known values
d. All above
Q. How it's possible to use a different placeholder through the parameter_______.
a. regression
b. classification
c. random_state
d. missing_values
Q. If you need a more powerful scaling feature, with a superior control on outliers and the possibility to select a quantile range, there's also the class________.
a. RobustScaler
b. DictVectorizer
c. LabelBinarizer
d. FeatureHasher
Q. scikit-learn also provides a class for per-sample normalization, Normalizer. It can apply________to each element of a dataset
a. max, l0 and l1 norms
b. max, l1 and l2 norms
c. max, l2 and l3 norms
d. max, l3 and l4 norms
Q. There are also many univariate methods that can be used in order to select the best features according to specific criteria based on________.
a. F-tests and p-values
b. chi-square
c. ANOVA
d. All above
Q. ________performs a PCA with non-linearly separable data sets.
a. SparsePCA
b. KernelPCA
c. SVD
d. None of the Mentioned