標題: Titlebook: Machine Learning and Knowledge Discovery in Databases; European Conference, Yasemin Altun,Kamalika Das,Sa?o D?eroski Conference proceedings [打印本頁] 作者: 航天飛機 時間: 2025-3-21 17:36
書目名稱Machine Learning and Knowledge Discovery in Databases影響因子(影響力)
書目名稱Machine Learning and Knowledge Discovery in Databases影響因子(影響力)學(xué)科排名
書目名稱Machine Learning and Knowledge Discovery in Databases網(wǎng)絡(luò)公開度
書目名稱Machine Learning and Knowledge Discovery in Databases網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Machine Learning and Knowledge Discovery in Databases被引頻次
書目名稱Machine Learning and Knowledge Discovery in Databases被引頻次學(xué)科排名
書目名稱Machine Learning and Knowledge Discovery in Databases年度引用
書目名稱Machine Learning and Knowledge Discovery in Databases年度引用學(xué)科排名
書目名稱Machine Learning and Knowledge Discovery in Databases讀者反饋
書目名稱Machine Learning and Knowledge Discovery in Databases讀者反饋學(xué)科排名
作者: 反對 時間: 2025-3-21 23:00
Jianing Zhao,Daniel M. Runfola,Peter Kempergaben mit einem mittleren Schwierigkeitsgrad w?hlen. Versucht beispielsweise ein Jugendlicher sportliche Leistungen im Hochsprung zu erbringen, so kann er die Sprunglatte unterschiedlich hoch auflegen. Bei einem realistischen Anspruchsniveau wird er eine H?he w?hlen, die ihm Anstrengung abverlangt, 作者: Folklore 時間: 2025-3-22 01:58 作者: 分發(fā) 時間: 2025-3-22 05:27 作者: 減去 時間: 2025-3-22 08:58 作者: 不規(guī)則的跳動 時間: 2025-3-22 16:00
Automatic Detection and Recognition of Individuals in Patterned Speciession (or Linear SVM) classifier to recognize the individuals. We primarily test and evaluate our framework on a camera trap tiger image dataset that contains images that vary in overall image quality, animal pose, scale and lighting. We also evaluate our recognition system on zebra and jaguar images作者: CLASH 時間: 2025-3-22 19:05 作者: 委派 時間: 2025-3-22 21:38
CREST - Risk Prediction for Clostridium Difficile Infection Using Multimodal Data Miningns these features into three sets: time-invariant, time-variant, and temporal synopsis features. CREST then learns classifiers for each set of features, evaluating their relative effectiveness. Lastly, CREST employs a second-order meta learning process to ensemble these classifiers for optimized est作者: 旋轉(zhuǎn)一周 時間: 2025-3-23 03:35
DC-Prophet: Predicting Catastrophic Machine Failures in ,ata,entersF.-score (The ideal value of F.-score is 1, indicating perfect predictions. Also, the intuition behind F.-score is to value “Recall” about three times more than “Precision” [.].) of 0.88 (out of 1). On average, DC-Prophet outperforms other classical machine learning methods by 39.45% in F.-score.作者: Vertical 時間: 2025-3-23 08:53
Event Detection and Summarization Using Phrase Networkas a clustering of high-frequency phrases extracted from text. All trending topics are then identified based on temporal spikes of the phrase cluster frequencies. PhraseNet thus filters out high-confidence events from other trending topics using number of peaks and variance of peak intensity. We eva作者: Junction 時間: 2025-3-23 11:16 作者: 顛簸下上 時間: 2025-3-23 16:53
Have It Both Ways—From A/B Testing to A&B Testing with Exceptional Model Miningant A where the general population prefers variant B, and vice versa. This data science technique is applied on data from StudyPortals, a global study choice platform that ran an A/B test on the design of aspects of their website.作者: Nebulous 時間: 2025-3-23 21:58
Koopman Spectral Kernels for Comparing Complex Dynamics: Application to Multiagent Sport Playsassified, e.g., by the success or failure of the shot. We mapped the latent dynamic characteristics of multiple attacker-defender distances to the feature space using our kernels and then evaluated the scorability of the play by using the features in different classification models.作者: 樣式 時間: 2025-3-23 23:00 作者: 膽小懦夫 時間: 2025-3-24 06:03
Predicting Self-reported Customer Satisfaction of Interactions with a Corporate Call Centerfunction is optimized to map the ranking scores to actual survey satisfaction scores. This approach produces more accurate predictions than standard regression and classification approaches that directly fit the survey scores with call data, and can be easily generalized to other customer satisfacti作者: Postmenopause 時間: 2025-3-24 08:33 作者: 蟄伏 時間: 2025-3-24 14:31
0302-9743 group discovery; time series and streams; transfer and multi-task learning; unsupervised and semisupervised learning.. Part III: applied data science track; nectar track; and demo track..978-3-319-71272-7978-3-319-71273-4Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 小淡水魚 時間: 2025-3-24 18:30
. Das Lehrbuch ist somit sowohl für Einsteiger als auch für Studierende und Dozenten, die sich vertieft mit der Lern- und Ged?chtnispsychologie befassen, geeignet..Eine Begleit-Website auf www.lehrbuch-psychologie.de bietet Lern-Tools für Studierende und Materialien für Dozenten..978-3-642-33866-3Series ISSN 0937-7433 Series E-ISSN 2512-5214 作者: G-spot 時間: 2025-3-24 22:17 作者: Commonwealth 時間: 2025-3-25 01:17 作者: 橢圓 時間: 2025-3-25 04:23 作者: Cardiac-Output 時間: 2025-3-25 11:16 作者: 表否定 時間: 2025-3-25 12:35
Di Wu,Boyu Wang,Doina Precup,Benoit Boulet. Das Lehrbuch ist somit sowohl für Einsteiger als auch für Studierende und Dozenten, die sich vertieft mit der Lern- und Ged?chtnispsychologie befassen, geeignet..Eine Begleit-Website auf www.lehrbuch-psychologie.de bietet Lern-Tools für Studierende und Materialien für Dozenten..978-3-642-33866-3Series ISSN 0937-7433 Series E-ISSN 2512-5214 作者: gerrymander 時間: 2025-3-25 19:22
Cansu Sen,Thomas Hartvigsen,Elke Rundensteiner,Kajal Claypool. Das Lehrbuch ist somit sowohl für Einsteiger als auch für Studierende und Dozenten, die sich vertieft mit der Lern- und Ged?chtnispsychologie befassen, geeignet..Eine Begleit-Website auf www.lehrbuch-psychologie.de bietet Lern-Tools für Studierende und Materialien für Dozenten..978-3-642-33866-3Series ISSN 0937-7433 Series E-ISSN 2512-5214 作者: 窩轉(zhuǎn)脊椎動物 時間: 2025-3-25 21:34
You-Luen Lee,Da-Cheng Juan,Xuan-An Tseng,Yu-Ting Chen,Shih-Chieh Chang. Das Lehrbuch ist somit sowohl für Einsteiger als auch für Studierende und Dozenten, die sich vertieft mit der Lern- und Ged?chtnispsychologie befassen, geeignet..Eine Begleit-Website auf www.lehrbuch-psychologie.de bietet Lern-Tools für Studierende und Materialien für Dozenten..978-3-642-33866-3Series ISSN 0937-7433 Series E-ISSN 2512-5214 作者: MANIA 時間: 2025-3-26 02:56 作者: 飛來飛去真休 時間: 2025-3-26 04:21 作者: Surgeon 時間: 2025-3-26 10:33 作者: HARD 時間: 2025-3-26 15:03
Wouter Duivesteijn,Tara Farzami,Thijs Putman,Evertjan Peer,Hilde J. P. Weerts,Jasper N. Adegeest,Ger. Das Lehrbuch ist somit sowohl für Einsteiger als auch für Studierende und Dozenten, die sich vertieft mit der Lern- und Ged?chtnispsychologie befassen, geeignet..Eine Begleit-Website auf www.lehrbuch-psychologie.de bietet Lern-Tools für Studierende und Materialien für Dozenten..978-3-642-33866-3Series ISSN 0937-7433 Series E-ISSN 2512-5214 作者: cushion 時間: 2025-3-26 16:48 作者: 小說 時間: 2025-3-26 23:06 作者: Nefarious 時間: 2025-3-27 01:16
A Novel Framework for Online Sales Burst Predictionhe seasonal and categorical features of sales burst. Based on the real data from JD.com, we conduct extensive experiments and discover that the proposed model makes a relative MSE improvement of 71% and 30% over LSTM and ARMA.作者: 悲痛 時間: 2025-3-27 09:14
Analyzing Granger Causality in Climate Data with Time Series Classification Methodsatasets from the area of climate-vegetation dynamics. The results indicate that specialized time series classification methods are able to improve existing inference procedures. Substantial differences are observed among the methods that were tested.作者: Palpable 時間: 2025-3-27 12:14
Probabilistic Inference of Twitter Users’ Age Based on What They Followdetermining the age of Twitter users from data that is native to the Twitter ecosystem. The key idea is to use a Bayesian framework to generalise ground-truth age information from a few Twitter users to the entire network based on what/whom they follow. Our approach scales to inferring the age of 700 million Twitter accounts with high accuracy.作者: Graphite 時間: 2025-3-27 15:07 作者: Mirage 時間: 2025-3-27 18:11 作者: Synovial-Fluid 時間: 2025-3-28 00:29 作者: 小蟲 時間: 2025-3-28 04:10
Optimal Client Recommendation for Market Makers in Illiquid Financial Productst recommendations for a particular bond that needs to be traded, ranked by probability of interest. We show that a model based on Latent Dirichlet Allocation offers promising performance to deliver relevant recommendations for sales traders.作者: 思考而得 時間: 2025-3-28 09:50 作者: Monolithic 時間: 2025-3-28 13:20
Conference proceedings 2017covery in Databases, ECML PKDD 2017, held in Skopje, Macedonia, in September 2017.?.The total of 101 regular papers presented in part I and part II was carefully reviewed and selected from 364 submissions; there are 47 papers in the applied data science, nectar and demo track.?.The contributions wer作者: enterprise 時間: 2025-3-28 18:22 作者: 懸掛 時間: 2025-3-28 21:10 作者: cumber 時間: 2025-3-29 01:49
Automatic Detection and Recognition of Individuals in Patterned SpeciesWidespread usage of camera traps has led to large volumes of collected images, making manual processing of visual content hard to manage. In this work, we develop a framework for automatic detection and recognition of individuals in different patterned species like tigers, zebras and jaguars. Most e作者: SHRIK 時間: 2025-3-29 04:13
Boosting Based Multiple Kernel Learning and Transfer Regression for Electricity Load Forecasting weather conditions, lagged values, and day types may affect electricity load consumption. We propose to use multiple kernel learning (MKL) for electricity load forecasting, as it provides more flexibilities than traditional kernel methods. Computation time is an important issue for short-term load 作者: 天真 時間: 2025-3-29 07:40 作者: 進入 時間: 2025-3-29 13:51
DC-Prophet: Predicting Catastrophic Machine Failures in ,ata,entersincrease the reliability of a datacenter? To answer these questions, we have studied what are probably the largest, publicly available datacenter traces, containing more than . events from . machines. Among these samples, we observe and categorize three types of machine failures, all of which are ca作者: 紳士 時間: 2025-3-29 18:06
Disjoint-Support Factors and Seasonality Estimation in E-Commercef sales every year, to make this forecast. In e-commerce setting, where the catalog of items is much larger than brick and mortar stores and hence includes a lot of items with short history, it is infeasible to compute seasonality for items individually. It is customary in these cases to use ideas f作者: 禍害隱伏 時間: 2025-3-29 20:09
Event Detection and Summarization Using Phrase Networkmely challenging because of the subtle difference between “events” and trending topics, the definitive rarity of these events, and the complexity of modern Internet’s text data. Existing approaches often utilize topic modeling technique and keywords frequency to detect events on Twitter, which have 作者: 不利 時間: 2025-3-30 02:59 作者: 油膏 時間: 2025-3-30 07:25
Have It Both Ways—From A/B Testing to A&B Testing with Exceptional Model Miningach test subject is presented with one of the two variants, and the measure of success is aggregated per variant. The variant of the product associated with the most success is retained, while the other variant is discarded. This, however, presumes that the company producing the products only has en作者: Ancillary 時間: 2025-3-30 12:15 作者: 貨物 時間: 2025-3-30 14:32
Modeling the Temporal Nature of Human Behavior for Demographics Predictionion is however often absent from mobile phone datasets, limiting the operational impact of the datasets. For these reasons, there has been a growing interest in predicting demographic information from mobile phone metadata. Previous work focused on creating increasingly advanced features to be model作者: Hormones 時間: 2025-3-30 19:53 作者: AGATE 時間: 2025-3-30 21:08 作者: Host142 時間: 2025-3-31 03:41 作者: elastic 時間: 2025-3-31 06:35 作者: BOLT 時間: 2025-3-31 11:35
