weka data mining

Algorithm Introduction NBC is one of the most widely used classification algorithms. The naive Bayes model originated from classical mathematical theory and has a solid mathematical foundation and stable classification efficiency. At the same time, the NBC model requires a very small number of metrics, which are not sensitive to missing data and the algorithm is simpler than the latency. Algorithm if Given the target value, attributes are mutually in

Algorithm Overview NBC is one of the most widely used classification algorithms. The naive Bayes model originated from classical mathematical theory and has a solid mathematical foundation and stable classification efficiency. At the same time, the NBC model requires few parameters, which are not sensitive to missing data and the algorithm is relatively simple. Algorithm hypothesis Given the target value, attributes are mutually independent. Algorith

Data analysis and miningBaidu MTC is an industry-leading mobile application testing service platform, providing solutions for the costs, technologies, and efficiency problems faced by developers in mobile application testing. At the same time, we will share the industry's leading Baidu technology, written by Baidu employees and industry leaders.1. Overview 1.1 the key to the success of a mobile app is marketing and product design, the core of

Label: What exactly is data mining? obviously data mining is not magic,Data Mining is the use of complex mathematical algorithms, so that we can use the computer's powerful computing power to sift through a large number of detai

hypothesis is obviously too strong,This is not necessarily the case. The use of the mean variance method also has similar problems. Therefore, the data normalization this step is not necessary to do, the specific problem to be seen. Normalization first in the case of a very large number of dimensions, you can prevent a certain dimension or some of the dimensions of the data impact too much, and then the pr

enterprises. With the rapid development of computer technology, network technology, communication technology, and Internet technology and the popularization of e-commerce, office automation, management information systems, and Internet, business operation processes of enterprises are increasingly automated, A large amount of data is generated during the enterprise's operation. These data and the resulting

0 S T S + T Sum Q + S R + T P = q + S + T + R Now let's look at the similarity: Q and T. That is, similarity measurement: d (I, j) = (q + T)/P = (q + T)/(q + S + T + r) Conversely, the opposite sex is a different measurement value .. That is, S and R, D (I, j) = (S + r)/P Of course, what we calculate is symmetric binary. What is a symmetric Binary Attribute? Both are meaningful and important in reality. Next, asymmetric binary similarity is assumed