Types of Classification
- [Baisis of Classification - GeeksforGeeks]
- Overview
In statistics, classification is the process of identifying which category an observation belongs to. For example, classifying an email as "spam" or "non-spam".
For performing statistical analysis, various kinds of data are gathered by the investigator or analyst. The information gathered is usually in raw form which is difficult to analyze.
To make the analysis meaningful and easy, the raw data is converted or classified into different categories based on their characteristics.
This grouping of data into different categories or classes with similar or homogeneous characteristics is known as the Classification of Data.
Each division or class of the gathered data is known as a Class. The different basis of classification of statistical information are Geographical, Chronological, Qualitative (Simple and Manifold), and Quantitative or Numerical.
Here are some types of classification:
- Quantitative classification: Classifies data according to measurable characteristics, such as height or weight.
- Chronological classification: Groups data according to time, such as years, months, or weeks.
- Interval data: Measures data along a numerical scale with equal distances between values.
Data can also be classified into quantitative, qualitative, geographical, or temporal groups.
- Four Types of Data Classification
In statistics, data is typically classified into four types: Nominal, Ordinal, Interval, Ratio.
These types of data have different properties and characteristics. The choice of which type to use depends on the nature of the data and the research question being addressed.
Interval data is used in many quantitative studies that calculate demographic information, test scores, or credit ratings.
Qualitative data is collected when recording information that categorizes observations. There are three types of qualitative variables: Categorical, Binary, Ordinal.
With these data types, you're often interested in the proportions of each category.
- Classification in AI
In AI, classification is a supervised ML technique that involves training systems to categorize data into labels or classes.
Classification is one of two main types of supervised ML techniques (regression the other). Classification models predict a class label, such as whether a customer will return or not, whether a certain transaction represents fraud or not, or whether a certain image is a car or not.
Classification models use a combination of algebra and statistical analysis to predict a class label. For example, a classification model might predict whether a customer will return, if a transaction is fraudulent, or if an image is a car.
To create an AI skill to classify documents, you can follow these steps:
- Choose document classification
- Name and describe the AI skill
- Review the security permissions
- Create a model
- Create the categories or types of documents the skill will classify
- Upload training documents that meet the listed requirements for each document type
- Save changes and click Train model
During training, the model will divide the documents into training and test documents.
[More to come ...]
