One of the machine learning tasks is supervised learning. In supervised learning we infer a function from labeled training data. The goal of supervised learning algorithms is learning a good hypothesis that minimizes the sum of the errors. A wide range of supervised alg More
One of the machine learning tasks is supervised learning. In supervised learning we infer a function from labeled training data. The goal of supervised learning algorithms is learning a good hypothesis that minimizes the sum of the errors. A wide range of supervised algorithms is available such as decision tress, SVM, and KNN methods. In this paper we focus on decision tree algorithms. When we use the decision tree algorithms, the data is partitioned by axis- aligned hyper planes. The geometric concept of decision tree algorithms is relative to separability problems in computational geometry. One of the famous problems in separability concept is computing the maximum bichromatic discrepancy problem. There exists an -time algorithm to compute the maximum bichromatic discrepancy in d dimensions. This problem is closely relative to decision trees in machine learning. We implement this problem in 1, 2, 3 and d dimension. Also, we implement the C4.5 algorithm. The experiments showed that results of this algorithm and C4.5 algorithm are comparable.
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One of the learning methods in machine learning and pattern recognition is supervised learning. In supervised learning and in two-category problems, the available educational data labels include positive and negative categories. The goal of the supervised learning algor More
One of the learning methods in machine learning and pattern recognition is supervised learning. In supervised learning and in two-category problems, the available educational data labels include positive and negative categories. The goal of the supervised learning algorithm is to calculate a hypothesis that can separate positive and negative data with the least amount of error. In this article, among all supervised learning algorithms, we focus on the performance of decision trees. The geometric view of the decision tree brings us closer to the concept of separability in computational geometry. Among all the available resolution algorithms related to the decision tree, we raise the problem of calculating the rectangle with the maximum difference of two colors and implement the algorithm in one, two, three and m dimensions, where m represents the number of data features. The implementation result shows that this algorithm is competitive with the well-known C4.5 algorithm.
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MIMO technology offers a wide range of transmission rates for modern wireless LANs. In order to improve the performance of the rate control module, statistical information on the history of state and usage of each transmission rate is maintained at the MAC layer to help More
MIMO technology offers a wide range of transmission rates for modern wireless LANs. In order to improve the performance of the rate control module, statistical information on the history of state and usage of each transmission rate is maintained at the MAC layer to help determine the rate at which future packets are sent. However, the great diversity of transmission rates in the 802.11n and 802.11ac standards imposes an overhead for updating this information. In this article, to reduce the state space of transmission rates while keeping statistics approximately up to date for each rate, a method for clustering rates is presented so that when sending a packet over a transmission rate, statistical information relating to all the rates belonging to the same cluster is updated. As a result, statistics for a greater number of rates can be updated even when sending a fewer number of packets. We implemented our proposed mechanism in the Linux kernel environment and evaluated its performance under different conditions on an experimental testbed deployed in our research laboratory. The results show that the proposed method outperforms the de-facto Minstrel-HT rate control mechanism in terms of throughput and number of successful transmissions.
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