This paper proposes the use of a new binary decision tree, which we call a soft decision tree, to improve generalization performance compared to the conventional ‘hard’ decision tree method that is used to cluster context-dependent model parameters in statistical parametric speech synthesis. We apply the method to improve the modeling of fundamental frequency, which is an important factor in sy...

Decision trees have been widely used in data mining and machine learning as a comprehensible knowledge representation. Originally the method to construct decision tree follows greedy approach which results in local tree and classification rules. Ant Colony Optimization (ACO) is a metaheuristic approach used to get more optimal solution compared to other methods from large search space. In propo...

Intrusion detection technology exists a lot of problems, such as low performance, low intelligent level, high false alarm rate, high false negative rate and so on. There is a need to develop some robust decision tree in order to produce effective decision rules from the attacked data. In this paper, ID3 decision tree classification method is used to build an effective decision tree for intrusio...

Penelitian ini melakukan penerapan algoritma decision tree. perusahaan kurang menganalisa penjualan barang dan stok persediaan didalam gudang. jadi jenis penelitian yakni memprediksi dengan konsep data mining sample bulan lalu. Tujuan untuk mengetahui produk apa yang paling diminati konsumen harus direstok, agar terkontrol. Metode akan digunakan malakukan penerapkan tree adalah menggunakan meto...

Decision tree algorithm (DT) is a commonly used data mining method for classification and regression. DT repeatedly divides dataset into pure subsets based on impurity measurements such as entropy Gini. Then relatively “pure” partitions consisting of observations with the (almost) same class are obtained. Gini index one representative indices measuring data. However, does not take...

Clinical decision requires reasoning in the presence of imperfect data. DTs are a well-known support tool, owing to their interpretability, fundamental safety-critical contexts such as medical diagnosis. However, learning from uncertain data leads poor generalization, and generating predictions for hinders prediction accuracy. Several methods have suggested potential probabilistic decisions at ...

Cancer is a major health issue that affects individuals all over the world. This disease has claimed lives of many people, and will continue to do so in future. Breast cancer recently surpassed cervical as most frequent among women both industrialized developing countries it now second leading cause mortality women. A high number die each year result this disease. significantly easier treat if ...

Different types of malicious attacks have been increasing simultaneously and become a serious issue for cybersecurity. Most leverage domain URLs as an attack communications medium compromise users into victim phishing or spam. We take advantage machine learning methods to detect the maliciousness automatically using three features: DNS-based, lexical, semantic features. The proposed approach ex...