Which of the following represents the collection of data that is arranged in a specific order for an Ai model?
dataset
feature
data analysis
class label
dataset
The answer is "dataset". A dataset represents a collection of data that is arranged in a specific order for an AI model. It includes both the input data (features) and the corresponding output data (class labels). Data analysis involves examining and interpreting the data in a dataset to gain insights and make informed decisions. But specifically, the collection of data itself is referred to as a dataset.
The collection of data that is arranged in a specific order for an AI model is called a "dataset". To understand this, let's break down the other options as well:
1. Feature: A feature, in the context of AI, refers to an individual measurable property or characteristic of a dataset that is used for training an AI model. It represents a particular aspect or attribute of the data.
2. Data analysis: Data analysis is the process of inspecting, cleaning, transforming, and modeling data in order to discover useful information, draw conclusions, and support decision-making. It involves various techniques to understand patterns, relationships, and insights from the data.
3. Class label: A class label, also known as a target variable, is a specific category or group to which each data point belongs. In supervised learning, the AI model is trained to predict or classify data based on the class labels assigned to them.
Therefore, out of the options provided, "dataset" is the correct term that represents the collection of data arranged in a specific order for an AI model. It encompasses all the relevant features, class labels, and any additional information required for training and evaluation of the AI model.