Data Mining in Agriculture

Data mining is a process of extracting hidden information and knowledge that people do not know in advance and have potential utilization value from a large number of noisy, incomplete, fuzzy, and random data. It is the integration of multiple discipline involving database technology, artificial intelligence, mathematical statistics, machine learning, pattern recognition, high-performance computing, knowledge engineering, neural networks, information retrieval, information visualization, and so on.

Introduction

Data mining is the process of retrieving hidden information from a database and translating it into a usable structure for later use. Figure 1 shows the data mining process and Fig. 2shows the different data mining techniques, where, ANN (Artificial Neural Network), SVM (Support Vector Machine), DT (Decision Tree), BN (Bayesian Networks), GA (Genetic Algorithm), HM (Hierarchical Methods), PM (Partitioning Methods), DBM (Density-based Methods), MBM (Model-based.