[White Paper Available] What is the Relationship Between Training Data and Machine Learning?
Having a large amount of training data is not necessarily good. What constitutes training data that enhances AI accuracy?
In machine learning, which is a method of AI, an essential factor for improving accuracy is the "quality of training data." For humans, having two or three examples of training data may seem sufficient for making judgments to some extent. However, for AI, deriving accurate answers from such limited data is challenging. Why is that the case? This document will explain the mechanism of machine learning and the reasons in detail. [Contents] ■ The 3 Steps of AI (Artificial Intelligence) - Training Data as an Important "Input" ■ What Training Data Means in AI's Machine Learning ■ The Relationship Between Training Data and Machine Learning - What Machine Learning is Doing ■ Challenges in Creating Appropriate Training Data ■ The Unique Challenges of "Fraud Investigation" and "Auditing" Supported by FRONTEO's AI, Strengths and Usage of Each AI ■ AI Specialized for the Purpose of "Discovery," FRONTEO's "KIBIT" *For more details, please download the PDF or feel free to contact us.
Inquire About This Product
basic information
For more details, please download the PDF or feel free to contact us.
Price range
Delivery Time
Applications/Examples of results
For more details, please download the PDF or feel free to contact us.
catalog（1）
Download All Catalogs
Company information
FRONTEO supports the judgments of experts in various fields who confront social issues day and night through the provision of its proprietary specialized AI, "KIBIT." This creates a starting point for innovation. Our unique natural language processing technology (patented in Japan and the U.S.) enables fast and high-precision analysis without relying on the amount of training data or computing power, unlike general-purpose AI. Additionally, by utilizing our patented technology that maps (visualizes the structure of) the analyzed information, "KIBIT" can directly influence the insights of experts. In recent years, KIBIT's technology has also been applied to hypothesis generation and target exploration in drug discovery. Through KIBIT's unique technology and approach, we are promoting social implementation in the fields of life sciences AI, business intelligence, economic security, and legal tech AI, with the aim of realizing our philosophy of "providing solutions that do not overlook risks and opportunities buried in records, and achieving fairness in the information society."