3 Classification and regression algorithms
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G. Venkataramana Sagar
Abstract
Machine learning algorithms for predicting or categorizing data include classification and regression techniques. Regression algorithms are used to forecast a continuous numerical value, such as the anticipated value of a stock price. In contrast, classification algorithms predict a discrete label, such as whether something is a cat or a dog. The accuracy of the algorithm’s predictions and classifications determines how effective a prediction or classification is. Decision trees, support vector machines, k-nearest neighbors, and naive Bayes are examples of standard classification techniques. Regression methods often used include generalized, polynomial, and linear regression.
Abstract
Machine learning algorithms for predicting or categorizing data include classification and regression techniques. Regression algorithms are used to forecast a continuous numerical value, such as the anticipated value of a stock price. In contrast, classification algorithms predict a discrete label, such as whether something is a cat or a dog. The accuracy of the algorithm’s predictions and classifications determines how effective a prediction or classification is. Decision trees, support vector machines, k-nearest neighbors, and naive Bayes are examples of standard classification techniques. Regression methods often used include generalized, polynomial, and linear regression.
Chapters in this book
- Frontmatter I
- Preface V
- Contents VII
- List of authors IX
- About the editors XIII
- 1 Introduction to artificial intelligence 1
- 2 AI technologies, tools, and industrial use cases 21
- 3 Classification and regression algorithms 53
- 4 Clustering and association algorithm 87
- 5 Reinforcement learning 109
- 6 Evaluation of AI model performance 125
- 7 Methods of cross-validation and bootstrapping 145
- 8 Meta-learning through ensemble approach: bagging, boosting, and random forest strategies 167
- 9 AI: issues, concerns, and ethical considerations 189
- 10 The future with AI and AI in action 213
- 11 A survey of AI in industry: from basic concepts to industrial and business applications 233
- 12 The intelligent implications of artificial intelligence-driven decision-making in business management 251
- 13 An innovative analysis of AI-powered automation techniques for business management 269
- 14 The smart and secured AI-powered strategies for optimizing processes in multi-vendor business applications 287
- 15 Utilizing AI technologies to enhance e-commerce business operations 309
- 16 Exploring the potential of artificial intelligence in wireless sensor networks 331
- 17 Exploring artificial intelligence techniques for enhanced sentiment analysis through data mining 345
- 18 Exploring the potential of artificial intelligence for automated sentiment 361
- 19 A novel blockchain-based artificial intelligence application for healthcare automation 373
- 20 Enhancing industrial efficiency with AI-enabled blockchain-based solutions 387
- Index 401
Chapters in this book
- Frontmatter I
- Preface V
- Contents VII
- List of authors IX
- About the editors XIII
- 1 Introduction to artificial intelligence 1
- 2 AI technologies, tools, and industrial use cases 21
- 3 Classification and regression algorithms 53
- 4 Clustering and association algorithm 87
- 5 Reinforcement learning 109
- 6 Evaluation of AI model performance 125
- 7 Methods of cross-validation and bootstrapping 145
- 8 Meta-learning through ensemble approach: bagging, boosting, and random forest strategies 167
- 9 AI: issues, concerns, and ethical considerations 189
- 10 The future with AI and AI in action 213
- 11 A survey of AI in industry: from basic concepts to industrial and business applications 233
- 12 The intelligent implications of artificial intelligence-driven decision-making in business management 251
- 13 An innovative analysis of AI-powered automation techniques for business management 269
- 14 The smart and secured AI-powered strategies for optimizing processes in multi-vendor business applications 287
- 15 Utilizing AI technologies to enhance e-commerce business operations 309
- 16 Exploring the potential of artificial intelligence in wireless sensor networks 331
- 17 Exploring artificial intelligence techniques for enhanced sentiment analysis through data mining 345
- 18 Exploring the potential of artificial intelligence for automated sentiment 361
- 19 A novel blockchain-based artificial intelligence application for healthcare automation 373
- 20 Enhancing industrial efficiency with AI-enabled blockchain-based solutions 387
- Index 401
