008 |
|
240618s2021 ch ad e 000 0 eng d |
020 |
|
|a9781799866619(ebk.)
|
020 |
|
|a9781799866602(pbk.)
|
020 |
|
|a9781799866596(hbk.)|cUS315
|
040 |
|
|aDLC|beng|dNOU
|
050 |
00
|
|aQA76.9.D343|b.H236 2021
|
095 |
|
|aLB|bLBF|cE020314|dQA76.9.D343|e.H236|y2021|fpeace0508|n8743|pBook|tLCC
|
100 |
1
|
|aPanda, Mrutyunjaya|eeditor.
|
245 |
00
|
|aHandbook of Research on Automated Feature Engineering and Advanced Applications in Data Science /|cMrutyunjaya Panda and Harekrishna Misra.
|
250 |
|
|a1st ed.
|
260 |
|
|aHershey, Pennsylvania :|bIGI Global,|c2021
|
300 |
|
|a392 pages :|billustrations ,Charts;|c30 cm.
|
504 |
|
|aIncludes bibliographical references and index.|aChapter 1. Feature engineering for various data types in data science -- Chapter 2. Feature selection techniques in high dimensional data with machine learning and deep learning -- Chapter 3. Hybrid attributes technique filter for the tracking of crowd behavior -- Chapter 4. Useful features for computer-aided diagnosis systems for melanoma detection using dermoscopic images -- Chapter 5. Development of rainfall prediction models using machine learning approaches for different agro-climatic zones -- Chapter 6. Multi-feature fusion and machine learning: a model for early detection of freezing of gait events in patients with Parkinson's disease -- Chapter 7. Developing brain tumor detection model using deep feature extraction via transfer learning -- Chapter 8. Feature engineering for structural health monitoring (SHM): a damage
|
650 |
0
|
|aData mining.
|
650 |
0
|
|aBig data|xIndustrial applications.
|
650 |
0
|
|aAutomatic data collection systems.
|
650 |
0
|
|aAutomatic classification.
|
700 |
1
|
|aMisra, H. K,|eeditor.
|
700 |
1
|
|aPanda, Mrutyunjaya.
|