Smartphones have become the ultimate 'personal' computer, yet despite this, general-purpose data-mining and knowledge discovery tools for mobile devices are surprisingly rare. DataLearner is a new data-mining application designed specifically for Android devices that imports the Weka data-mining engine and augments it with algorithms developed by Charles Sturt University. Moreover, DataLearner can be expanded with additional algorithms. Combined, DataLearner delivers 40 classification, clustering and association rule mining algorithms for model training and evaluation without need for cloud computing resources or network connectivity. It provides the same classification accuracy as PCs and laptops, while doing so with acceptable processing speed and consuming negligible battery life. With its ability to provide easy-to-use data-mining on a phone-size screen, DataLearner is a new portable, self-contained data-mining tool for remote, personalised and learning applications alike. DataLearner features four elements - this paper, the app available on Google Play, the GPL3-licensed source code on GitHub and a short video on YouTube.
翻译:智能手机已成为最终的“个人”计算机,然而,尽管如此,用于移动设备的通用数据挖掘和知识发现工具却出乎意料地少之又少。数据定位器是专为进口Weka数据挖掘引擎的Android装置设计的一个新的数据挖掘应用程序,该装置通过Charles Stutt大学开发的算法来进口Weka数据挖掘引擎并增加其数量。此外,数据定位器可以通过额外的算法加以扩展。数据定位器联合提供40种用于模型培训和评估的分类、集群和关联规则挖掘算法,而不需要云计算资源或网络连接。它提供与PC和膝上型计算机相同的分类精度,同时使用可接受的处理速度并消耗了可忽略的电池寿命。数据定位器具有在电话屏幕上提供方便使用的数据挖掘功能的能力,数据定位器是用于远程、个性化和学习应用程序的新的便携式、自成一体的数据采集数据挖掘工具。数据定位器有四个要素――这张纸上可用的应用程序、Google Play上可用的GPL3授权源码,以及一个在GitHutub上的短视频。