Titlebook: Soft Computing in Data Science; First International Michael W. Berry,Azlinah Mohamed,Bee Wah Yap Conference proceedings 2015 Springer Scie

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書目名稱Soft Computing in Data Science影響因子(影響力)




書目名稱Soft Computing in Data Science影響因子(影響力)學科排名




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書目名稱Soft Computing in Data Science網(wǎng)絡(luò)公開度學科排名




書目名稱Soft Computing in Data Science被引頻次




書目名稱Soft Computing in Data Science被引頻次學科排名




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書目名稱Soft Computing in Data Science年度引用學科排名




書目名稱Soft Computing in Data Science讀者反饋




書目名稱Soft Computing in Data Science讀者反饋學科排名

HEAVY

Arthropathy

Thanh van Do,Hai Thanh Nguyen,Nikolov Momchil,Van Thuan Do

啞巴

不發(fā)音

Comparisons of ADABOOST, KNN, SVM and Logistic Regression in Classification of Imbalanced Dataset%,Testing: 90.2%) and precision (Training:91.9%, Testing 90.5%) for training and testing data set. For random undersampling, no overfitting occurs only for ADABOOST and logistic regression. Logistic regression is the most stable classifier exhibiting consistent training an testing results.

EXPEL

Finding Significant Factors on World Ranking of e-Governments by Feature Selection Methods over KPIsnd studied using traditional statistical methods. In this paper, an alternative method by feature selection in data mining is proposed which computes quantitatively the relative importance of each KPI with respective to the predicted class, the rank. The main advantage of feature selection by data m

Condyle

Solving Curriculum Based Course Timetabling by Hybridizing Local Search Based Method within Harmony oth operators together. In addition, several harmony memory consideration rates were applied on those setups. The algorithms of all setups were tested on curriculum-based datasets taken from the International Timetabling Competition, ITC2007. The results demonstrated that our approach was able to pr

STANT

A Parallel Latent Semantic Indexing (LSI) Algorithm for Malay Hadith Translated Document Retrievalext files. The processing time during the pre-processing phase of the documents for the proposed parallel LSI is measured and compared to the sequential LSI algorithm. Our results show that processing time for pre-processing tasks using our proposed parallel LSI system is faster than sequential syst

MONY

Spongy-Bone