Predict the Main Factors that Affect the Vegetable Production in Palestine Using WEKA Data Mining Tool
الكلمات المفتاحية:Data Mining، K-means، EM Algorithm، Kohonen’s Self-Organizing Map (KSOM) and Clustering.
This research presents an applied study using data mining to discover some factors affecting agricultural vegetable production and predicting the yield production in Palestine. In this research, we are interested in finding some factors that will influence the agricultural production to increase the amount of production to benefit the farmers in particular and individual, society in general. To achieve this goal we used Waikato’s Knowledge Analysis Environment (WEKA) tool and algorithms such as K-Means, Kohonen’s Self Organizing Map (KSOM) and EM to identify the most influential factors that increase the production of agricultural vegetable. This research has proved that K-Means is worthwhile to increase the efficiency and reliability of the prediction process of determining the factors that affect the yield production and KSOM the most accurate to predict the yield production.
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