Machine Learning Practice · Quiz 1 · Jan 2024

Based on the above data, answer the given subquestions.

Choose the correct options to determine the count of NULL values in each column of a pandas DataFrame named ’df’

Based on the above data, answer the given subquestions.

Which option will help in selecting data of **odd indexed** columns only? (ie. age, parch are odd indexed 1 and 3 respectively)

Based on the above data, answer the given subquestions.

What is datatype of sex column in the given titanic dataset

Based on the above data, answer the given subquestions.

Which option will help in filtering data to find **females who are alive** after titanic incident?

Based on the above data, answer the given subquestions.

What is the given code below trying to accomplish for the given titanic dataset ?

You are working on a machine learning project that aims to predict housing prices based on various features of the houses. As the first step, you decide to perform exploratory data analysis and visualize the data to understand its structure and relationships. Which of the following visualization techniques or principles is LEAST likely to provide meaningful insights for this kind of regression problem?

A company collects 40000 samples (examples) to build a Machine Learning model for an application. They decide to use 30% of the total samples for testing (to be stored in the variable **testset**) and the rest 70% for training (to be stored in the variable **trainset**). They also want to sample the same set of samples across multiple runs. Which of the following line (statement) achieves this task? Assume that all samples are stored in the variable **data**.

Choose the option based on the following statements: Statement 1: The train-test split allows us to simulate the model’s performance on new data by reserving a portion of the dataset for testing. Statement 2: Separating the dataset into training and testing sets helps prevent data leakage, where information from the test set unintentionally influences the model during training. This ensures a fair assessment of the model’s generalization capabilities.

In which of the following scenarios is data cleaning most required?

Which of the following metrics indicate higher their value, better the regression model’s performance?

Suppose that we plot the histogram of numerical features in a data set. This reveals which of the following information?

Which of the following are valid loss functions for SGDClassifier?

Which of the following Evaluation metrics can be used in a regression problem?

Which of the following feature(s) will be selected in X_selected from X ?