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https://www.um.edu.mt/library/oar/handle/123456789/47822
Title: | Improving the performance of machine learning algorithms through increasing dataset size |
Authors: | Agius, Clayton |
Keywords: | Machine learning Big data Data sets Computer algorithms |
Issue Date: | 2019 |
Citation: | Agius, C. (2019). Improving the performance of machine learning algorithms through increasing dataset size (Bachelor's dissertation). |
Abstract: | Machine learning a very important field in computer science is utilized in many scientific domains and ever-widening range of human activities. Its main objective is to enable a machine to learn from past data, construct accurate predictive models and apply these models to a variety of problems such as classification. This ability has proven to be very effective in a variety of domains such as healthcare and business. One of the most important factors that determines if a Machine learning algorithm is successful in building a good predictive model or not, is the data available for analysis. Nowadays we are seeing a shift from having limited amount of available data to more data that we can store, analyse and process. In this study, a set of experiments were designed and implemented to investigate the effect of increasing dataset size given to a Machine learning algorithm. Several datasets, Machine learning algorithms and evaluation techniques where made use of. The datasets used were split up into a number of increasing data size segments, each of which analysed and evaluated in terms of accuracy, cost and other perspectives. Each experiment yielded a range of results which led to a set of conclusions of interest. Whilst by increasing the dataset size the processing power needed to analyse this data also increases; it cannot be said that increasing the data size always resulted in a better performance. Another aspect was that other variations such as Machine learning algorithms and evaluation techniques had an important effect on the performance when increasing dataset size. |
Description: | B.SC.SOFTWARE DEVELOPMENT |
URI: | https://www.um.edu.mt/library/oar/handle/123456789/47822 |
Appears in Collections: | Dissertations - FacICT - 2019 Dissertations - FacICTCIS - 2019 |
Files in This Item:
File | Description | Size | Format | |
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19BITSD001.pdf Restricted Access | 3.2 MB | Adobe PDF | View/Open Request a copy |
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