Data Pre-Processing for Visual Data Mining

Most Visual Data Mining tools use interactive 2D visualization methods in delivering the meaningful information from the data but when the high number of features, attributes and observations in a data set is large, the methods do not scale well and it is hard to visually determine the data set. This leads to the development of cooperative approach using a consensus theory based on feature selection algorithm, clustering for sampling and visualization for weight assignments in order to aggregate multivariate and multidimensional data sets. This allows visualization and then visual data mining without loss of classifier accuracy, thus resulting in a successful experiments with several high dimensional data sets.

• Feature Selection aims at choosing a subset of attributes that is sufficient to describe the data set. This process includes identifying and removing the irrelevant and redundant information. This method can be very helpful for Visual Data Mining as it reduces the load of handling large amount of data.
• Numerosity Reduction reduces number of objects based on their redundancy and description as expected by the experiment. 
• Dimensionality Reduction helps in reduction of attributes, this not only reduces the number of iteration linearly but also exponentially and hence the name explains it reduces the dimension that are irrelevant for the particular set of visualization or analysis that need to be performed. 
• Discretization and Quantization reduces the number of values for a given continuous attribute by dividing the range of the attribute into intervals. Interval labels can then be used to replace actual data values. Binning techniques is the most commonly used form of Quantization.
• Generalization is the process which abstracts a large set of task-relevant data in a database from low conceptual levels to higher ones. Generalization has some limitations like handling only dimensions of simple non-numeric data and measures of simple aggregated numeric values, lack of intelligent analysis, it can`t tell which dimensions should be used and what levels should the generalization reach. But it also includes one of the most simple way of reduction, that is; Generalization and specialization can be performed on a data cube by roll-up and drill-down.

Besides aggregation and filtering which are applied over the large data set or database technologies, can also be carried out by using Data Mining techniques. These techniques may involve database operations such as aggregation, sampling, or other method resulting into classification of data or the clusters as an output.

App with CRUD Functionality - User Management using IONIC Framework Phonegap/Cordova [Tutorial/An Overview]

This is a simple app to implement CRUD (Create Read Update Delete) functionality using IONIC Framework on the top of Phonegap/Cordova. This application is designed for Iphone, Android and Windows Phone but can also be deployed as Blackberry Application. I name it as AppCRUD targetting User Management. I have also added some extra perks like visualizing the User Data using Charts.js and Angular Charts.

In this application I have implemented an additional functionality which is Directive. Directives are the part of AngularJS Framework which helps developer to extend the standard functionality. In this application, use of directive is applied to the "Add/Edit User Template" to focus the first Input Element in our View. You can have a look in the "/www/js/directives.js" and yes we have to add this directives.js file to our base html file that is "index.html" as well as to our Module as a Dependency in "app.js" file.

Setting Up the Project

Installation Required:

• Node JS for NPM Packages
• Cordova
• IONIC Framework
• Android SDK (for the deployment to the Device/Emulator)
• IOS (you need a MAC for the deployment to the Device/Emulator)

Create Project Directory

Here's a link to the Github Repository IonicAppCRUD. You can either download a zip or simply clone it with Git Bash.

git clone https://github.com/DynamicRemo/IonicAppCRUD.git

Platform, Build and Deploy

cd IonicAppCRUD

After the navigation to the Project Directory, we can run our project with ionic serve command and the output will be displayed in the Browser.

ionic serve

Or we can have the App View just like the Mock Ups for IOS and Android, its a new cool feature by IONIC.

ionic serve --lab

Moreover, we can add IOS and Android Platform to our Project and can directly deploy to our Device.

ionic platform add android
ionic platform add ios

ionic run android
ionic run ios

Application Overview

Followings are the different views of Application: User Listing, User Add/Edit, User Delete, Reordering of User Listing and the Visualization of data using Angular Charts.

For feedbacks and discussion, please leave a comment. Thank You!