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Cutting Edge Data Analytical Tools
Published in Chong Ho Alex Yu, Data Mining and Exploration, 2022
Although IBM SPSS Statistics includes several data mining and predictive modeling tools, its primary function is to run traditional statistics. The major data mining software application offered by IBM is SPSS Modeler, which uses a flow-chart interface for quick development and deployment of predictive modeling. SPSS Modeler can be used for mining numeric data. For texting mining an additional module named SPSS Modeler Premium is needed. SPSS Modeler can be used as a standalone module on a local computer, but it can also be used in a distributed network (IBM 2020). Figure 3.10 displays a typical SPSS modeler project. Like many other modern data mining tools, SPSS modeler allows the user to drag and drop icons representing different functions into the canvas to generate a sequence of actions. In addition, SPSS Modeler offers many automated procedures, such as Auto Classifier, Auto Numeric, Auto Cluster, etc. (see Figure 3.10). In this example, after Auto Cluster is placed on the canvas, the system explores different clustering algorithms and then suggests the best solution to the user.
The impact of Big Data on making evidence-based decisions
Published in Matthias Dehmer, Frank Emmert-Streib, Frontiers in Data Science, 2017
Rodica Neamtu, Caitlin Kuhlman, Ramoza Ahsan, Elke Rundensteiner
SPSS Modeler is a data mining and text analytics software application from IBM. It provides a range of advanced algorithms and techniques, including text analytics, entity analytics, decision management, and optimization to deliver actionable insights in near real time.†
Bridging customer knowledge to innovative product development: a data mining approach
Published in International Journal of Production Research, 2019
Yuanzhu Zhan, Kim Hua Tan, Baofeng Huo
Table 6 shows the dataset to which decision tree modelling was applied. It includes 167 samples reflecting the respondents’ preferences for different smartphone features and types. For instance, the feature ‘color’ had five different options: (1) white (denoted CL1), (2) gold (CL2), (3) silver (CL3), (4) black (CL4), and (5) does not matter (CL5). In particular, the smartphone features could be seen as ‘If’, and the style was defined as ‘Then’. Decision tree modelling aimed to generate rules in a format, such as the kinds of features that led the respondents to choose the relevant type of smartphone product. This was achieved by splitting the data source into subsets according to attribute-value analysis. The C5.0 package was applied to analyze whether the respondents’ selections of particular features were related to their choice of smartphone type (i.e. purchase decision). IBM SPSS Modeler 18.0 was used to conduct the decision tree modelling. IBM SPSS Modeler 18.0 is a data mining software package that features visual programming and a data flow interface. It can work with various types of data and so provides organisations with extensive data mining capabilities to deal with various specific problems.
Style classification and prediction of residential buildings based on machine learning
Published in Journal of Asian Architecture and Building Engineering, 2020
Bing Xia, Xin Li, Hui Shi, Sichong Chen, Jiamei Chen
IBM SPSS Modeler is a leading data mining platform with graphical grammar as the user interface. It encapsulates the most advanced statistics and data mining technology to obtain prediction knowledge, and can provide data mining related full-process functions as data understanding, conversion, analysis, modeling, evaluation. SPSS Modeler uses a simple drag-and-drop method to quickly build data mining analysis models, including analysis algorithms from statistics, machine learning, artificial intelligence and other aspects, such as cluster analysis, discriminant analysis, neural networks, etc. (Xue and Chen 2019). It can achieve association and classification, prediction and other comprehensive mining and analysis functions.