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: Computational Intelligence in Data Science; 7th IFIP TC 12 Inter Mieczyslaw Lech Owoc,Felix Enigo Varghese Sicily,P Conference proceedings

[復(fù)制鏈接]
樓主: panache
11#
發(fā)表于 2025-3-23 11:57:58 | 只看該作者
12#
發(fā)表于 2025-3-23 15:31:14 | 只看該作者
Mieczyslaw Lech Owoc,Felix Enigo Varghese Sicily,P
13#
發(fā)表于 2025-3-23 18:44:29 | 只看該作者
14#
發(fā)表于 2025-3-24 00:13:03 | 只看該作者
15#
發(fā)表于 2025-3-24 05:34:38 | 只看該作者
https://doi.org/10.1007/978-3-658-27431-3 techniques. Designed for open-source collaboration, this solution is positioned for continuous improvement, adaptation to evolving needs, and addressing emerging challenges in the field of intelligent transportation and related domains. This paper represents a foundational step towards establishing
16#
發(fā)表于 2025-3-24 08:09:49 | 只看該作者
Arbeitsbereich Baumanagement – ic regression, SVM, stochastic gradient descent, decision trees, and ensemble models were conducted. In summary, this research contributes significantly to the ongoing battle against online toxicity and the promotion of more constructive online conversations. The RNN algorithm’s 99.47% accuracy rate
17#
發(fā)表于 2025-3-24 13:34:54 | 只看該作者
18#
發(fā)表于 2025-3-24 15:45:21 | 只看該作者
Die digitale Demokratie in der Schweizhese experiments, we attained exceptional F1 scores of 99% for RoBERTa, 98% for AlBERT, and 96% for BERT base. In contrast, traditional models like Logistic Regression achieved 93%, Random Forest 89%, and deep learning models such as LSTM, BiLSTM and CNN achieved 82%, 93% and 90%, respectively. The
19#
發(fā)表于 2025-3-24 19:32:59 | 只看該作者
20#
發(fā)表于 2025-3-25 01:57:04 | 只看該作者
Julian Bubel Dipl.-Ing.,Jürgen Grabend reduce complexity. This is leading to improved classification performance. The proposed work is evaluated on six machine-learning models. The features extracted achieving a consistent AUC-ROC score of 95%. The highest accuracy of 95% on the Cleveland dataset. Our proposed machine learning-based C
 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(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, 2025-10-7 11:12
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
隆回县| 集贤县| 宝山区| 石狮市| 买车| 冀州市| 专栏| 嘉兴市| 万年县| 伊春市| 黄大仙区| 安泽县| 类乌齐县| 沙田区| 阳泉市| 达日县| 秦皇岛市| 绿春县| 中山市| 延寿县| 白银市| 福海县| 阳山县| 焦作市| 平和县| 安平县| 青神县| 中山市| 西和县| 靖西县| 永昌县| 塔城市| 白玉县| 新昌县| 克拉玛依市| 北票市| 新绛县| 巴林右旗| 新巴尔虎右旗| 阿鲁科尔沁旗| 永泰县|