Veri Madenciliği Yöntemleri: Tarım Alanında Uygulamaları

Veri Madenciliği Yöntemleri: Tarım Alanında Uygulamaları (Data Mining Methods: Applications in the Field of Agriculture), edited by Assoc. Prof. Dr. Şenol Çelik serves as a comprehensive guide that utilises statistical methods and machine learning algorithms to transform raw data into valuable information within the agricultural sector. Data mining, which plays a critical role in enhancing the efficiency of modern agricultural production, is presented in this book through both its theoretical foundations and practical applications, supported by tools like the R programming language. Enriched by the contributions of eighteen dcademics  this 8-chapter work ddevotessignificant focus, particularly in its first four chapters, to the MARS (Multivariate Adaptive Regression Splines) algorithm, ensuring a deep understanding of the technique.

Furthermore, other key data mining methods ,such as CHAID CART  Artificial Neural Networks (ANN)  the C5.0 algorithm  K-Means  and Support Vector Machines , re discussed with detailed applications. The most distinctive feature of the study is its application of these complex techniques to real-world agricultural problems. It offers a wbroadspectrum of applications, from detecting Varroa infestation in apicinfestationsanalyzing sunfloweranalysingaracteristics, to predicting liv weight in small ruminants, classifying dairy cattle data, and conducting soil analysis. This work is an invaluableresourcee for academics and readersseekingh to approach agricultural research from a data science perspective.