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: https://gist.githubusercontent.com/curran/a08a1080b88344b0c8a7/raw/d546eaee765268bf2f4876
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: https://gist.githubusercontent.com/curran/a08a1080b88344b0c8a7/raw/d546eaee765268bf2f4876
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:
https://gist.githubusercontent.com/curran/a08a1080b88344b0c8a7/raw/d546eaee765268bf2f4876
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
Answer
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