Book
Modern Data Mining Algorithms in C++ and CUDA C Recent Developments in Feature Extraction and Selection Algorithms for Data Science
| Identifier | --timothymas-1561 |
|---|---|
| Penulis / Pengarang | Timothy Masters |
| Kata Kunci | Data Mining Data Science Algorithms |
| Tanggal Publikasi | 12 Feb 2020 |
| Bahasa | Bahasa Inggris |
| Abstrak / Deskripsi | serious data miners are often faced with thousands of candidate features for their prediction or classification application, with most of the features being of little or no value. Worse still, many of these features may be useful only in combination with certain other features while being practically worthless alone or in combination with most others. Some features may have enormous predictive power, but only within a small, specialized area of the feature space. The problems that plague modern data miners are endless. My own work over the last 20+ years in the financial market domain has involved an examination of decades of price data from hundreds or thousands of markets, searching for exploitable patterns of price movement. I could not have done it without having a large and up-to-date collection of data mining tools. Over my career, I have accumulated many such tools, and I still keep up to date with scientific journals, exploring the latest algorithms as they appear. In my recent book Data Mining Algorithms in C++, published by the Apress division of Springer, I presented many of my favorite algorithms. I now continue this presentation, divulging details and source code of key modules in my VarScreen variable screening program that has been made available for free download and frequently updated over the last few years. |
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| No | Nama Berkas | Format | Ukuran | Aksi |
|---|---|---|---|---|
| 1 | 2020 Modern Data Mining Algorithms in C++ and CUDA C Recent Developments in Feature Extraction and Selection Algorithms .pdf | application/pdf | 2,3 MB | ⬇️ Buka / Download |
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