Structured Data Classification MCQs - MCQ Village

Structured Data Classification MCQs

Hello friends in this post we are going discuss about Structured Data Classification Multiple choice question | Structured Data Classification Question Answer | Structured Data Classification TCS Fresco play dumps | Structured Data Classification Fresco play question answer | Structured Data Classification objective type question

1.Which of the given hyper parameter(s), when increased may cause random forest to over fit the data?

Answer : Depth of Tree

2.Pruning is a technique associated with

Answer : Decision tree

3.High classification accuracy always indicates a good classifier.

Answer : True

4.Categorical variables has

Answer : no logical order

5. Cross-validation technique will provide accurate results when the training set and the testing set are from two different populations.

Answer : True

6.Let’s assume, you are solving a classification problem with highly imbalanced class. The majority class is observed 99% of times in the training data. Which of the following is true when your model has 99% accuracy after taking the predictions on test data. ?

Answer : For imbalanced class problems, accuracy metric is not a good idea

7.Email spam detection is an example of

Answer : supervised classification

8.A technique used to depict the performance in a tabular form that has 2 dimensions namely “actual” and “predicted” sets of data.

Answer : Confusion Matrix

9.Choose the correct sequence for classifier building from the following:

Answer : Initialize -> Train – -> Predict–>Evaluate

10.The commonly used package for machine learning in python is

Answer : sklearn

11.A classifer that can compute using numeric as well as categorical values is

Answer : Decision Tree Classifier

12.Can we consider sentiment classification as a text classification problem?

Answer : yes

13.What kind of classification is the given case study(IRIS dataset)?Download the dataset from:
08c537c05e22e4b221/iris.csv to answer the question.

Answer : Multi class classification

14.Ensemble learning is used when you build component classifiers that are more accurate and independent from each other.

Answer : true

15.clustering is an example of

Answer : unsupervised classification

16.Model Tuning helps to increase the accuracy

Answer : True

17.Images and documents are examples of ______

Answer : Unstructured Data

18.Ordinal variables has

Answer : clear logical order

19.Which command is used to select all NUMERIC types in the dataset.Download the dataset from:
08c537c05e22e4b221/iris.csv to answer the question.

Answer : iris_num = iris_data.select_dtypes(include=[numpy.number])

20.The number of categorical attributes in the original dataset.Download the dataset from:
08c537c05e22e4b221/iris.csv to answer the question.

Answer : 3

21.Which classifier converges easily with less training data?

Answer : Naive Bayes Classifier

22.Imputing is a strategy to handle


23.classification where each data is mapped to more than one class is called

Answer : Binary Classification.

24.The fit(X, y) is used to

Answer : Train the Classifier

25.Supervised learning differs from unsupervised learning as supervised learning requires _

Answer : Labeled data

26.Clustering is a supervised classification.

Answer : False

27.Select the correct option which directly achieve multi-class classification (without support of binary classifiers).

Answer : K Nearest Neighbor

28.The classification where each data is mapped to more than one class is called _

Answer : Multi Label Classification

29.Email spam data is an example of _____

Answer : unstructed Data

30.The most widely used package for machine learning in Python is _

Answer : sklearn

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