[PDF] Top 20 SFLA Based Gene Selection Approach for Improving Cancer Classification Accuracy

... stage, SFLA is applied to gene ...that SFLA-FS enables to balance between exploration and exploitation, thus finding more important genes by taking advantage of the parameter adjustment and ... See full document

... the classification accuracy by reducing the number of misclassified samples, thereby reducing the complexity and time consumption in processing the gene expression ...on gene expression ... See full document

... (CR)-based classification with regularized least square was developed [31] to classify gene ...high classification accuracy and fast computational speed than the traditional ... See full document

... method based on research articles published in journals and conference ...strategy based on specific themes such as current research area in data quality, critical dimensions in data quality, data quality ... See full document

... new approach proposed to solve gene selection problem which combined MRMR, BA, and SVM ...This approach is a hybrid filter-wrapper approach. MRMR filter approach run in the ... See full document

... mann selection policy to achieve the uniform random ini- tialization and thus to make the whole PSABC approach have a better global search potential and capacity at the very ...new approach, some ... See full document

... perfect approach in detecting the code ...similarities based on statements written in programming ...an approach which detects the dependencies based on ...detected based on code ... See full document

... normalization approach that addresses the complexity of stop-words ...earlier approach - (NORMS or NORMalizer of Schemata), NORMSTOP shows up to 13% improvement in annotation recall ...perfect ... See full document

... and classification. Classification is a machine learning technique used to predict the correlation between data samples and ...several classification techniques, among which are: Support Vector ... See full document

... proposed approach is to extract informative outcome from feature selection method to find a subset of informative features that have smaller size and better classification accuracy compare to ... See full document

... text classification systems [28]. It also concentrated on the ontology based systems which are used for categorizing the documents on the extracted ...hybrid approach shows higher accurate rate, ... See full document

... scheduling techniques, which generates MapReduce job output as per nearby Datanodes. The resource-based locality-aware processing focuses over data placement technique, which can be executed after a MapReduce job ... See full document

... The information gathered from various sources is integrated to identify the risks associated with the user’s health. The main objective of employing fusion is to produce a fused result that provides the most reliable ... See full document

... in education is to base choices on technological possibilities rather than educational needs. In developing countries where higher education is fraught with serious challenges at multiple levels, there is increasing ... See full document

... Akadej, Nakornthip & Pizzanu [4] had done a research in retrieving software requirements by using use case terms. There are three main processes during the retrieval of use case which include storage, retrieval and ... See full document

... From the result, the biomedical literature is retrieved by using the preprocessing method, retrieved techniques, and clustering techniques. The Multi-Kernel Fuzzy c Means (MK-FCM) technique is utilized for clustering in ... See full document

... code- based approaches is that most of them are language dependent [10], so testing process will become more complicated in cases where the program is written in various programming ... See full document

... Big data is the captured of information from our life day by day. Data from Mobile devices, the Internet, Finance, Streaming, Sensors, and Science are the top six data drivers. With the fast rises in computing storage ... See full document

... In addition, there has been no study to discuss, the gap that became an important point in this study with previous research is to know and observe factors related to awareness and attit[r] ... See full document

... ELM is a very fast, simple and efficient learning algorithm for training the SLFNs. Unlike that of in traditional learning methods used to train SLFNs, in ELM the output weight matrix of the network is calculated ... See full document