This Supplementary Information further describes the methods used in DEEPer by providing additional details and proofs. Section A proves the validity of the indirect pruning algorithms, Algorithms 1 (proved in A.1) and 2 (in A.2), and derives their time complexity (A.3). Section B describes some details of implementation, relating to the application of perturbations (B.1) and the choice of prun...

Saat ini UMKM (Usaha Mikro Kecil dan Menengah) sangat berperan penting dalam peningkatan perekonomian negara berkembang seperti Indonesia. Pengusaha-pengusaha telah terbukti memiliki ketangguhan kemampuan menghadapi krisis ekonomi. Upaya meningkatkan atau mengoptimalisasikan pemasaran kemasan, promosi, kondisi produk, bahan legalitas perijinan layak tidaknya makanan itu beredar di pasaran harus...

Forward pruning, or selectively searching a subset of moves, is now commonly used in game-playing programs to reduce the number of nodes searched with manageable risk. Forward pruning techniques should consider how pruning errors in a game-tree search propagate to the root to minimize the risk of making errors. In this paper, we explore forward pruning using theoretical analyses and Monte Carlo...

Decision tree technology has proven to be a valuable way of capturing human decision making within a computer. It has long been a popular artificial intelligence(AI) technique. During the 1980s, it was one of the primary ways for creating an AI system. During the early part of the 1990s, it somewhat fell out of favor, as did the entire AI field in general. However, during the later 1990s, with ...

A large-scale pruning study was established in the winter of 1999 to2000 at seven different sites on Green Diamond Resource Company forestlands in Humboldt County. The objective of this study was to determine the effects of pruning on increment, epicormic sprouting, stem taper, heartwood formation, and bear damage on these young trees. Pruning treatments varied pruning severity and were usually...

Most speech recognition systems search through large finite state machines to find the most likely path, or hypothesis. Efficient search in these large spaces requires pruning of some hypotheses. Popular pruning techniques include probability pruning which keeps only hypotheses whose probability falls within a prescribed factor from the most likely one, and rank pruning which keeps only a presc...

The pruning phase is one of the necessary steps in decision tree induction. Existing pruning algorithms tend to have some or all of the following difficulties: 1) lack of theoretical support; 2) high computational complexity; 3) dependence on validation; 4) complicated implementation. The 2-norm pruning algorithm proposed here addresses all of the above difficulties. This paper demonstrates the...

Many researchers have shown that ensemble methods such as Boosting and Bagging improve the accuracy of classification. Boosting and Bagging perform well with unstable learning algorithms such as neural networks or decision trees. Pruning decision tree classifiers is intended to make trees simpler and more comprehensible and avoid over-fitting. However it is known that pruning individual classif...

A three-dimensional non-linear finite-element model (FEM) was constructed using a commercial software (ATENA-Studio) to investigate the transverse load distribution behavior of adjacent precast prestressed concrete box-girder bridges. An innovative connection between box girders used, where post-tensioning applied at top flanges only eliminating need for intermediate diaphragms. The FEM validat...