找回密碼
 To register

QQ登錄

只需一步,快速開(kāi)始

掃一掃,訪(fǎng)問(wèn)微社區(qū)

打印 上一主題 下一主題

Titlebook: Machine Learning and Data Mining in Pattern Recognition; 13th International C Petra Perner Conference proceedings 2017 Springer Internation

[復(fù)制鏈接]
樓主: 不讓做的事
31#
發(fā)表于 2025-3-26 21:33:47 | 只看該作者
Qualitative and Descriptive Topic Extraction from Movie Reviews Using LDA,ion from text reviews using Latent Dirichlet Allocation (LDA) based topic models. Our models extract distinct qualitative and descriptive topics by combining text reviews and movie ratings in a joint probabilistic model. We evaluate our models on an IMDB dataset and illustrate its performance through comparison of topics.
32#
發(fā)表于 2025-3-27 01:38:14 | 只看該作者
33#
發(fā)表于 2025-3-27 07:48:34 | 只看該作者
34#
發(fā)表于 2025-3-27 09:43:14 | 只看該作者
0302-9743 ing to specific data mining methods for the different multi-media data types such as image mining, text mining, video mining, and Web mining..978-3-319-62415-0978-3-319-62416-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
35#
發(fā)表于 2025-3-27 17:40:31 | 只看該作者
0302-9743 Data Mining in Pattern Recognition, MLDM 2017, held in New York, NY, USA in July/August 2017.The 31 full papers presented in this book were carefully reviewed and selected from 150 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern min
36#
發(fā)表于 2025-3-27 20:30:19 | 只看該作者
37#
發(fā)表于 2025-3-27 23:16:36 | 只看該作者
Machine Learning-as-a-Service and Its Application to Medical Informatics,ontribution, we provide a comparison of several state-of-the-art Machine Learning-as-a-Service platforms along with their capabilities in medical informatics. In addition, we performed several analyses to examine the qualitative and quantitative attributes of two Machine Learning-as-a-Service environments namely “BigML” and “Algorithmia”.
38#
發(fā)表于 2025-3-28 04:22:25 | 只看該作者
Prediction of Insurance Claim Severity Loss Using Regression Models, the final loss value was also predicted with an error of 0.440 using FFNN regression model. We also demonstrate the use of lasso regularization to avoid over-fitting for some of the regression models.
39#
發(fā)表于 2025-3-28 10:19:38 | 只看該作者
40#
發(fā)表于 2025-3-28 12:07:33 | 只看該作者
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛(ài)論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評(píng) 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國(guó)際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-14 21:46
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
元谋县| 淳化县| 舒兰市| 新巴尔虎右旗| 玉龙| 垣曲县| 尤溪县| 甘孜县| 和龙市| 阿勒泰市| 湘阴县| 霍林郭勒市| 嘉祥县| 南靖县| 木里| 永新县| 宣化县| 光泽县| 龙南县| 西华县| 莒南县| 尚义县| 淮南市| 仲巴县| 门源| 福鼎市| 团风县| 苍梧县| 湖南省| 揭西县| 互助| 台北县| 建始县| 阳新县| 江津市| 红原县| 林周县| 筠连县| 察隅县| 弥渡县| 儋州市|