Descriptive statistics machine learning

How is statistics used in machine learning?
Statistics is a core component of machine learning.
It helps you draw meaningful conclusions by analyzing raw data.
In this article on Statistics for Machine Learning, you covered all the critical concepts that are widely used to make sense of data..
What is descriptive approach in machine learning?
Descriptive Analysis in Machine Learning is all about perspective to understand the data and its different existing patterns.
Basically, it is part of four types of Data Analysis concepts._{Oct 1, 2021}.
What is descriptive learning in machine learning?
Descriptive Analysis in Machine Learning is all about perspective to understand the data and its different existing patterns.
Basically, it is part of four types of Data Analysis concepts._{Oct 1, 2021}.
What is descriptive statistics for dataset?
Descriptive statistics refers to a set of methods used to summarize and describe the main features of a dataset, such as its central tendency, variability, and distribution.
These methods provide an overview of the data and help identify patterns and relationships._{Oct 19, 2023}.
Which statistics is used in machine learning?
Thus, one of the two subfields of statistics used in machine learning model, namely statistical hypothesis tests and estimation statistics is leveraged for interpretation and comparison of the results between different hyperparameter configurations..

Normal Distribution

The normal distributionis one of the most important concepts in statistics since nearly all statistical tests require normally distributed data

Central Tendency

In statistics we have to deal with the mean, mode and the median. These are also called the “Central Tendency

Measures of Variability

The most popular variability measures are the range, interquartile range (IQR), variance, and standard deviation

Variance and Standard Deviation

The standard deviation and the variance also measure, like the Range and IQR, how spread apart our data is (e.g the dispersion)

Modality

The modality of a distribution is determined by the number of peaks it contains

Skewness

Skewnessis a measurement of the symmetry of a distribution. Therefore it describes how much a distribution differs from a normal distribution

Kurtosis

Kurtosis measures whether your dataset is heavy-tailed or light-tailed compared to a normal distribution

Summary of Descriptive Statistics For Machine Learning

This post gave you a proper introduction to descriptive statistics for machine learning

How to use descriptive statistics in Azure Machine Learning Studio?

The data comes from the UCI Machine Learning Repository

Once you have logged into your Azure Machine Learning Studio account, click on the EXPERIMENTS option, listed on the left sidebar, followed by the NEW button

Next, click on the blank experiment and give the name Descriptive Statistics to the workspace

The following screen will be displayed

What are descriptive statistics in machine learning?

Descriptive statistics area subset of statistical methods that are used to summarize data

In machine learning, data is often complex and large, making it difficult to understand without some type of summary

Descriptive statistics can help us understand the data by summarizing it in a way that is easy to interpret

What is the difference between machine learning and statistics?

This is due to machine learning being all about making predictions

On the other hand, statistics is all about drawing conclusions from data, which is a necessary initial step

In this post, you will learn about the most important descriptive statistical concepts