However, most techniques in mining do not consider knowledge of the quality of the database. In this work, we show how to incorporate into classification mining recent advances in the data quality field that vie
Data classification is the process of categorizing feature data and comparing it with reference templates, often using machine learning techniques to generate a matching score for decision making in biometrics authentication methods. AI generated definition based on:Computers & Security,2016 ...
Statistical data-mining (DM) and machine learning (ML) are promising tools to assist in the analysis of complex dataset. In recent decades, in the precision of agricultural development, plant phenomics study is crucial for high-throughput phenotyping of local crop cultivars. Therefore, integrated or...
The mining process described above is performed in the training set, and only those patterns found significant using the Bonferroni are then tested in the test set. In addition to these two steps we evaluate the discovered patterns by their ability to classify several additional drugs (Table 1,...
Time Series Classification (TSC) is an important and challenging problem in data mining. With the increase of time series data availability, hundreds of TS
this process is labour intensive and requires significant domain knowledge to identify relevant features. In the case of high-dimensional data, feature generation is even more challenging due to the high computation cost of evaluating the potentially exponential number of different feature sets. Another...
The package provides support for modeling and simulating data streams as well as an extensible framework for implementing, interfacing and experimenting with algorithms for various data stream mining tasks. The main advantage of stream is that it seamlessly integrates with the large existing infrastructure...
Classification is a two-step process; a learning step and a prediction step. In the learning step, the model is developed based on given training data. In the prediction step, the model is used to predict the response to given data. A Decision tree is one of the easiest and most popular...
Data mining (DM) is a process of discovering knowledge (interesting patterns) from huge datasets and is currently procuring extent deal of focus also became a prominent analysis tool.1 In recent days, data mining techniques are applied in various fields such as stock market analysis, telecommunicat...
The induction of classifiers from data sets of pre-classified instances, usually calledtraining data, is one of the fundamental tasks in Machine Learning (Stanke and Waack, 2003). The process of modelling from training data, i.e., building up the mapping from observed features/attributes to cor...