找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Data Mining with SPSS Modeler; Theory, Exercises an Tilo Wendler,S?ren Gr?ttrup Textbook 2021Latest edition Springer Nature Switzerland AG

[復(fù)制鏈接]
樓主: Buren
41#
發(fā)表于 2025-3-28 18:07:50 | 只看該作者
Appendix,hich involves familiarizing with the meaning of the different variables in the dataset. This chapter lists all datasets used in this book together with an explanation of their background as well as a description and the meaning of the different variables included.
42#
發(fā)表于 2025-3-28 22:44:18 | 只看該作者
43#
發(fā)表于 2025-3-29 00:47:40 | 只看該作者
rn about basic and more advanced data mining, and put this knowledge into practice. This revised and updated second edition includes a new chapter on imbalanced data and resampling techniques as well as an extensive case study on the cross-industry standard process for data mining.978-3-030-54339-6978-3-030-54338-9
44#
發(fā)表于 2025-3-29 06:36:23 | 只看該作者
Ryan C. Knoper M.D.,Daniel Valentino M.D.ality of the model..After finishing this chapter, the reader can:.The interested reader should have a look especially at the following papers: We recommend van Buuren (.), McKnight et al. (.), Guyon and Elisseeff (.), and Kotsiantis et al. (.) for the data preparation and IBM (.) for the CRISP-DM mo
45#
發(fā)表于 2025-3-29 10:48:49 | 只看該作者
46#
發(fā)表于 2025-3-29 12:27:18 | 只看該作者
Basic Functions of the SPSS Modeler,raphical representation of the results, e.g., the frequency distribution or the significance of a statistical test..Using the datasets provided with this book, this chapter gives an outline of how to import the data into an IBM SPSS Modeler stream and perform basic operations on the dataset..After f
47#
發(fā)表于 2025-3-29 15:55:13 | 只看該作者
48#
發(fā)表于 2025-3-29 21:45:54 | 只看該作者
49#
發(fā)表于 2025-3-30 03:52:39 | 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 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| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2026-1-26 12:02
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
贞丰县| 津南区| 明溪县| 海丰县| 延长县| 蓝田县| 济宁市| 镇赉县| 津南区| 休宁县| 巍山| 婺源县| 赤峰市| 甘德县| 浠水县| 云林县| 孟州市| 福海县| 武鸣县| 凌源市| 江津市| 南投县| 潢川县| 田阳县| 五台县| 辉县市| 永州市| 大化| 石渠县| 斗六市| 綦江县| 峡江县| 五指山市| 三亚市| 云梦县| 封开县| 比如县| 邯郸县| 突泉县| 新乐市| 田阳县|