標(biāo)題: Titlebook: Data Mining; 16th Australasian Co Rafiqul Islam,Yun‘Sing Koh,Zahidul Islam Conference proceedings 2019 Springer Nature Singapore Pte Ltd. 2 [打印本頁(yè)] 作者: 相持不下 時(shí)間: 2025-3-21 17:19
書目名稱Data Mining影響因子(影響力)
書目名稱Data Mining影響因子(影響力)學(xué)科排名
書目名稱Data Mining網(wǎng)絡(luò)公開度
書目名稱Data Mining網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Data Mining被引頻次
書目名稱Data Mining被引頻次學(xué)科排名
書目名稱Data Mining年度引用
書目名稱Data Mining年度引用學(xué)科排名
書目名稱Data Mining讀者反饋
書目名稱Data Mining讀者反饋學(xué)科排名
作者: Ccu106 時(shí)間: 2025-3-21 20:25
An Approach to Compress and Represents Time Series Data and Its Application in Electric Power Utilitrom utility companies’ substations by comparing the compressed outputs to the original forms. The result is a new discretized set that is lower in volume and can represent the time series succinctly with a minimal loss that can be managed.作者: 抗原 時(shí)間: 2025-3-22 01:30
Conference proceedings 2019e organized in topical sections on classification task;?transport, environment, and energy; applied data mining; privacy and clustering; statistics in data science; health, software and smartphone; image data mining; industry showcase..作者: Etymology 時(shí)間: 2025-3-22 07:26
1865-0929 papers are organized in topical sections on classification task;?transport, environment, and energy; applied data mining; privacy and clustering; statistics in data science; health, software and smartphone; image data mining; industry showcase..978-981-13-6660-4978-981-13-6661-1Series ISSN 1865-0929 Series E-ISSN 1865-0937 作者: 煩擾 時(shí)間: 2025-3-22 08:44 作者: COWER 時(shí)間: 2025-3-22 13:22 作者: COWER 時(shí)間: 2025-3-22 20:47 作者: Ophthalmologist 時(shí)間: 2025-3-22 21:27 作者: Exclaim 時(shí)間: 2025-3-23 03:11
Technology, Work and Globalizationrom utility companies’ substations by comparing the compressed outputs to the original forms. The result is a new discretized set that is lower in volume and can represent the time series succinctly with a minimal loss that can be managed.作者: EWER 時(shí)間: 2025-3-23 07:06 作者: 光亮 時(shí)間: 2025-3-23 09:56
Collaboration as a Mode of Labourcan be focused on time. The . game setup and its replay data are used in extensive experimental testing. The proposed method has shown to outperform the accuracy of both a past machine learning approach and a professional team of human observers.作者: 樹木中 時(shí)間: 2025-3-23 15:50 作者: BRINK 時(shí)間: 2025-3-23 21:08 作者: 吹牛者 時(shí)間: 2025-3-23 23:06 作者: BARB 時(shí)間: 2025-3-24 06:11
Data Mining978-981-13-6661-1Series ISSN 1865-0929 Series E-ISSN 1865-0937 作者: TAP 時(shí)間: 2025-3-24 10:09 作者: 向外 時(shí)間: 2025-3-24 11:44 作者: Demonstrate 時(shí)間: 2025-3-24 15:54
978-981-13-6660-4Springer Nature Singapore Pte Ltd. 2019作者: Aboveboard 時(shí)間: 2025-3-24 20:42 作者: 秘密會(huì)議 時(shí)間: 2025-3-25 00:54
https://doi.org/10.1057/9780230503922ification, linear SVM has shown remarkable efficiency for classifying documents due to its superior performance. It tries to create the best decision boundary that enables the separation of positive and negative documents with the largest margin hyperplane. However, in most cases there are regions i作者: labyrinth 時(shí)間: 2025-3-25 05:05
Wolfgang Goerigk,Friedemann Simonso known as HDLSS problem), non-linearity, and data types tend are complex. A large number of dimensionality reduction techniques developed, but, unfortunately, not efficient with small-sample (observation) size dataset. To overcome the pitfalls of the sample-size and dimensionality this study emplo作者: SYN 時(shí)間: 2025-3-25 08:13
https://doi.org/10.1007/10703260nominal and numerical attributes. However, their need to test the suitability of every attribute at every tree node, in addition to testing every possible split-point for every numerical attribute can be expensive computationally, particularly for datasets with high dimensionality. This paper propos作者: 貧窮地活 時(shí)間: 2025-3-25 14:07 作者: 詢問(wèn) 時(shí)間: 2025-3-25 16:21 作者: 大罵 時(shí)間: 2025-3-25 22:18 作者: 免除責(zé)任 時(shí)間: 2025-3-26 01:46
Carole Bouchard,Jean-Fran?ois Omhoverutant exposure has generally been wanting. In recent years this has motivated the development of several cheap, portable air quality monitoring instruments. However, these instruments also tend to be unreliable, and thus the raw measurements require preprocessing to make accurate predictions of actu作者: GUILT 時(shí)間: 2025-3-26 05:12 作者: 真實(shí)的人 時(shí)間: 2025-3-26 10:41 作者: Irksome 時(shí)間: 2025-3-26 16:39
and the Encounter of Performanceis paper proposes a new hybrid imputation method to effectively deal with the missing data issue of the Mobility in Cities Database (MCD) to construct city mobility indices. The hybrid method integrates the advantages of decision trees and fuzzy clustering into an iterative algorithm for missing dat作者: Conscientious 時(shí)間: 2025-3-26 18:54 作者: 自制 時(shí)間: 2025-3-27 00:03
Noyale Colin,Stefanie Sachsenmaieribility of their trained model. As different cities usually contain a different set of location features (district names, apartment names), most existing mass appraisal methods have to train a new model from scratch for different cities or regions. As a result, these approaches require massive data 作者: APEX 時(shí)間: 2025-3-27 02:46
A Case for Collaborative Staff Developmentding conditions of vector mosquitos. We use Hamiltonian Monte Carlo sampling to estimate a seasonal Gaussian process modeling infection rate, and aperiodic basis coefficients for the rate of an “outbreak level” of infection beyond seasonal trends across two separate regions. We use this outbreak lev作者: 核心 時(shí)間: 2025-3-27 05:59 作者: 險(xiǎn)代理人 時(shí)間: 2025-3-27 12:25
Multiple Support Vector Machines for Binary Text Classification Based on Sliding Window Techniqueification, linear SVM has shown remarkable efficiency for classifying documents due to its superior performance. It tries to create the best decision boundary that enables the separation of positive and negative documents with the largest margin hyperplane. However, in most cases there are regions i作者: 搜集 時(shí)間: 2025-3-27 14:25 作者: Gratulate 時(shí)間: 2025-3-27 19:50 作者: Chronic 時(shí)間: 2025-3-27 22:18 作者: 苦惱 時(shí)間: 2025-3-28 02:46
Categorical Features Transformation with Compact One-Hot Encoder for Fraud Detection in Distributed mbination of numeric as well as mixed attributes. Usually, numeric format data gives better performance for classification, regression and clustering algorithms. However, many machine learning problems have categorical, or nominal features, rather than numeric features only. In addition, some machin作者: 出價(jià) 時(shí)間: 2025-3-28 09:31
Combining Machine Learning and Statistical Disclosure Control to Promote Open Dataed variables in its open crash data for privacy-preserving data mining. Instead of making arbitrary decisions in variable aggregation and using perturbation to guard against reidentification attacks at the cost of data distortion, we creatively drew upon feature engineering and dimensionality reduct作者: 江湖騙子 時(shí)間: 2025-3-28 14:05 作者: 我不重要 時(shí)間: 2025-3-28 17:25
An Approach to Compress and Represents Time Series Data and Its Application in Electric Power Utilitmbolically which can be used for time series’ classification or anomaly detection. The proposed method is tested using the time series data obtained from utility companies’ substations by comparing the compressed outputs to the original forms. The result is a new discretized set that is lower in vol作者: violate 時(shí)間: 2025-3-28 20:30 作者: 裝飾 時(shí)間: 2025-3-29 00:54
A Hybrid Missing Data Imputation Method for Constructing City Mobility Indicesis paper proposes a new hybrid imputation method to effectively deal with the missing data issue of the Mobility in Cities Database (MCD) to construct city mobility indices. The hybrid method integrates the advantages of decision trees and fuzzy clustering into an iterative algorithm for missing dat作者: 放棄 時(shí)間: 2025-3-29 04:44
A Novel Learning-to-Rank Method for Automated Camera Movement Control in E-Sports Spectatinge fans watch tournament games through a camera of the observer. Bigger tournaments hire professional human observers with high-end tools to monitor important events in the game map for broadcasting the game. This setup is prone to errors. It results in missing important events within the game and lo作者: 使?jié)M足 時(shí)間: 2025-3-29 10:44 作者: Ambulatory 時(shí)間: 2025-3-29 13:09
Statistical Models of Dengue Feverding conditions of vector mosquitos. We use Hamiltonian Monte Carlo sampling to estimate a seasonal Gaussian process modeling infection rate, and aperiodic basis coefficients for the rate of an “outbreak level” of infection beyond seasonal trends across two separate regions. We use this outbreak lev作者: 呼吸 時(shí)間: 2025-3-29 19:37 作者: 火光在搖曳 時(shí)間: 2025-3-29 23:21 作者: infinite 時(shí)間: 2025-3-30 00:58 作者: 貿(mào)易 時(shí)間: 2025-3-30 05:13
https://doi.org/10.1007/10703260eely-available datasets from the UCI data repository. Results from this testing indicate the two components of SPAARC combined have minimal effect on decision tree classification accuracy yet reduce model build times by as much as 69%.作者: Motilin 時(shí)間: 2025-3-30 11:12 作者: wangle 時(shí)間: 2025-3-30 12:21
Carole Bouchard,Jean-Fran?ois Omhoverty based on 11 quasi-identifiers, with less than 3% suppression, compared with only 3-anonymity based on no more than 8 quasi-identifiers with far more than 3% suppression commonly reported in literature. Furthermore, our method enabled random forest classifier to achieve 0.996 for AUC and 0.895 for作者: Ingratiate 時(shí)間: 2025-3-30 19:42 作者: 徹底明白 時(shí)間: 2025-3-30 21:38 作者: insecticide 時(shí)間: 2025-3-31 02:19 作者: Enthralling 時(shí)間: 2025-3-31 05:17 作者: Vertebra 時(shí)間: 2025-3-31 12:33
Multiple Support Vector Machines for Binary Text Classification Based on Sliding Window Techniquet vector machines are proposed that can effectively deal with the uncertain boundary and improve predictive accuracy in linear SVM for data having uncertainties. This is achieved by dividing the training documents into three distinct regions (positive, boundary, and negative regions) based on a slid作者: FORGO 時(shí)間: 2025-3-31 16:44 作者: 騙子 時(shí)間: 2025-3-31 18:00
