作者: 吹牛者 時間: 2025-3-21 20:31
Multiple-Knowledge Representations in concept learning,owledge level to build an . correct . description of it. This approach is illustrated through our GEM system which learns concepts in a numerical attribute space using a Neural Network representation as the deep knowledge level and symbolic rules as the shallow level.作者: ear-canal 時間: 2025-3-22 00:45 作者: Enliven 時間: 2025-3-22 05:55 作者: NADIR 時間: 2025-3-22 09:39
Learning abstract planning cases,troduced model. An empirical study in the domain of process planning in mechanical engineering shows significant improvements in planning efficiency through learning abstract cases while an explanation-based learning method only causes a very slight improvement.作者: 討好美人 時間: 2025-3-22 15:42 作者: 演繹 時間: 2025-3-22 19:25 作者: 討好美人 時間: 2025-3-23 01:12 作者: 心胸狹窄 時間: 2025-3-23 03:48 作者: euphoria 時間: 2025-3-23 07:10
Analogical logic program synthesis from examples,d, two programs are said to be similar if they share a common explanation structure at an abstract level. Using this notion of similarity, we formalize an analogical logic program synthesis and show that our algorithm based on a framework of model inference can identify a desired program.作者: colony 時間: 2025-3-23 16:36
The effect of numeric features on the scalability of inductive learning programs,amined discrete and finite feature spaces. In order to test these results, a set of experiments was carried out, involving one artificial and two real data sets. The artificial data set introduces a near-worst-case situation for the examined algorithms, while the real data sets provide an indication of their average-case behaviour.作者: Chameleon 時間: 2025-3-23 20:22
Reasoning and learning in probabilistic and possibilistic networks: An overview,learning such networks from data..Whereas Bayesian networks and Markov networks are well-known for a couple of years, we also outline the perspectives of possibilistic networks as a tool for the efficient information-compressed treatment of uncertain . imprecise knowledge.作者: micronutrients 時間: 2025-3-24 00:21
Pruning multivariate decision trees by hyperplane merging,ional decision trees. Nearly unexplored remains the large domain of . methods, where a new decision test (derived from previous decision tests) replaces a subtree. This paper presents an approach to multivariate-tree pruning based on merging the decision hyperplanes, and demonstrates its performance on artificial and benchmark data.作者: Employee 時間: 2025-3-24 05:32 作者: cocoon 時間: 2025-3-24 09:51
0302-9743 e papers address all current aspects in the area of machine learning; also logic programming, planning, reasoning, and algorithmic issues are touched upon.978-3-540-59286-0978-3-540-49232-0Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: inferno 時間: 2025-3-24 14:08
Conference proceedings 1995 four invited papers the volume presents revised versions of 14 long papers and 26 short papers selected from a total of 104 submissions. The papers address all current aspects in the area of machine learning; also logic programming, planning, reasoning, and algorithmic issues are touched upon.作者: 清晰 時間: 2025-3-24 17:40
Reasoning and learning in probabilistic and possibilistic networks: An overview,of probabilistic and possibilistic networks, respectively, and consider knowledge representation and independence as well as evidence propagation and learning such networks from data..Whereas Bayesian networks and Markov networks are well-known for a couple of years, we also outline the perspectives作者: AGONY 時間: 2025-3-24 20:28 作者: SPECT 時間: 2025-3-25 02:20 作者: Aromatic 時間: 2025-3-25 04:00
Learning abstract planning cases,om given concrete cases. For this purpose, we have developed a new abstraction methodology that allows to completely . of a planning case, when the concrete and abstract languages are given by the user. Furthermore, we present a learning algorithm which is correct and complete with respect to the in作者: CRAB 時間: 2025-3-25 08:34
The role of prototypicality in exemplar-based learning,perties approach, and a similarity-based approach, and suggests measures that implement the different approaches. The proposed measures are tested in a set of experiments. The results of the experiments show that prototypicality serves as a good storing filter in storage reduction algorithms; combin作者: Friction 時間: 2025-3-25 13:45
Specialization of recursive predicates,sible to specialize or remove any of the clauses in a refutation of a negative example without excluding any positive examples. A previously proposed solution to this problem is to apply program transformation in order to obtain non-recursive target predicates from recursive ones. However, the appli作者: BROTH 時間: 2025-3-25 18:29 作者: 暴露他抗議 時間: 2025-3-25 22:48 作者: commute 時間: 2025-3-26 01:54 作者: QUAIL 時間: 2025-3-26 06:33 作者: 不可磨滅 時間: 2025-3-26 11:32 作者: comely 時間: 2025-3-26 14:11
The power of decision tables,spaces possible, and usually they are easy to understand. Experimental results show that on artificial and real-world domains containing only discrete features, IDTM, an algorithm inducing decision tables, can sometimes outperform state-of-the-art algorithms such as C4.5. Surprisingly, performance i作者: Prostatism 時間: 2025-3-26 19:24
Pruning multivariate decision trees by hyperplane merging,y contain binary tests questioning to what side of a hyperplane the example lies. Most of these algorithms use . mechanisms similar to those of traditional decision trees. Nearly unexplored remains the large domain of . methods, where a new decision test (derived from previous decision tests) replac作者: extemporaneous 時間: 2025-3-26 21:14
Multiple-Knowledge Representations in concept learning,nown that biases used in learning algorithms directly affect their performance as well as their comprehensibility. A critical problem is that, most of the time, the most “comprehensible” representations are not the best performer in terms of classification! In this paper, we argue that concept learn作者: exophthalmos 時間: 2025-3-27 02:58
The effect of numeric features on the scalability of inductive learning programs,resents the results of a theoretical and experimental investigation of the scalability of four well-known empirical concept learning programs. In particular it examines the effect of using numeric features in the training set. The theoretical part of the work involved a detailed worst-case computati作者: 抱負(fù) 時間: 2025-3-27 07:51
Analogical logic program synthesis from examples,mples, the task of our algorithm is to find a program which explains the examples correctly and is similar to the source program. Although we can define a notion of similarity in various ways, we consider a class of similarities from the viewpoint of how examples are explained by a program. In a wor作者: Bombast 時間: 2025-3-27 12:33
A guided tour through hypothesis spaces in ILP,llions of hypotheses for even simple learning problems. Controlling hypothesis spaces by biases requires knowledge on the effects and applicability of biases in different domains. This knowledge can be gained experimentally by comparing the size of hypothesis spaces with respect to the language bias作者: Ankylo- 時間: 2025-3-27 15:14 作者: 障礙物 時間: 2025-3-27 20:29
Specialization of recursive predicates,tions of positive examples. In contrast to its predecessor SPECTRE, the new algorithm is not limited to specializing clauses defining one predicate only, but may specialize clauses defining multiple predicates. Furthermore, the positive and negative examples are no longer required to be instances of作者: Dysarthria 時間: 2025-3-28 02:00
The power of decision tables,the number of instances, the number of features, and the number of label values. The time for incremental cross-validation is independent of the number of folds chosen, hence leave-one-out cross-validation and ten-fold cross-validation take the same time.作者: 小隔間 時間: 2025-3-28 06:04
https://doi.org/10.1007/3-540-59286-5Case-Based Learning; Concept-Learning; Fallbasiertes Lernen; Genetische Algorithmen; Lern-Algorithmen; Ma作者: Override 時間: 2025-3-28 10:05 作者: 彎彎曲曲 時間: 2025-3-28 11:05
A distributed genetic algorithm improving the generalization behavior of neural networks,standard learning algorithms like e.g. backpropagation. In this paper a distributed genetic algorithm is designed and used to improve the network‘s generalization capabilities by reducing the number of different weights in the neural network.作者: 郊外 時間: 2025-3-28 16:21 作者: 消音器 時間: 2025-3-28 22:21
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/m/image/620758.jpg作者: 集合 時間: 2025-3-28 23:49 作者: LINES 時間: 2025-3-29 04:56 作者: MURAL 時間: 2025-3-29 09:35
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10樓作者: 散開 時間: 2025-4-2 04:43
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