Home » Microsoft » DP-100 » Which two modules can you use?
You are analyzing a dataset by using Azure Machine Learning Studio.
You need to generate a statistical summary that contains the p-value and the unique count for each feature column.
Which two modules can you use? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
A. Computer Linear Correlation
B. Export Count Table
C. Execute Python Script
D. Convert to Indicator Values
E. Summarize Data
Correct Answer: BE
Explanation/Reference:
The Export Count Table module is provided for backward compatibility with experiments that use the Build Count Table (deprecated) and Count Featurizer (deprecated) modules.
E: Summarize Data statistics are useful when you want to understand the characteristics of the complete dataset. For example, you might need to know:
How many missing values are there in each column?
How many unique values are there in a feature column?
What is the mean and standard deviation for each column?
The module calculates the important scores for each column, and returns a row of summary statistics for each variable (data column) provided as input.
Incorrect Answers:
A: The Compute Linear Correlation module in Azure Machine Learning Studio is used to compute a set of Pearson correlation coefficients for each possible pair of variables in the input dataset.
C: With Python, you can perform tasks that aren’t currently supported by existing Studio modules such as:
Visualizing data using matplotlib
Using Python libraries to enumerate datasets and models in your workspace
Reading, loading, and manipulating data from sources not supported by the Import Data module
D: The purpose of the Convert to Indicator Values module is to convert columns that contain categorical values into a series of binary indicator columns that can more easily be used as features in a machine learning model.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/export-count-table https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/summarize-data