„Machine Learning Models“

Suchergebnisse

3.650 Treffer

• Predictive Supervised Machine Learning Models for Diabetes Mellitus
  Muhammad, L. J. ; Algehyne, Ebrahem A. ; Usman, Sani Sharif
• Regional Flood Frequency Analysis Through Some Machine Learning Models in Semi-arid Regions
  Allahbakhshian-Farsani, Pezhman ; Vafakhah, Mehdi ; Khosravi-Farsani, Hadi ; Hertig, Elke
• Landslide hazard risk modeling in north-west of Iran using optimized machine learning models
  Jamali, Ali
• Data analytics – models and algorithms for intelligent data analysis
  Runkler, Thomas A. 2020 Springer Vieweg
• Physics-informed machine learning for backbone identification in discrete fracture networks
  Srinivasan, Shriram ; Cawi, Eric ; Hyman, Jeffrey ; Osthus, Dave ; Hagberg, Aric ; Viswanathan, Hari ; Srinivasan, Gowri
• Construction and Comparison of Predictive Models for Length of Stay after Total Knee Arthroplasty: Regression Model and Machine Learning Analysis Based on 1,826 Cases in a Single Singapore Center
  Li, Hui ; Jiao, Juyang ; Zhang, Shutao ; Tang, Haozheng ; Qu, Xinhua ; Yue, Bing
• Microvascular Complications in Type-2 Diabetes: A Review of Statistical Techniques and Machine Learning Models
  Sambyal, Nitigya ; Saini, Poonam ; Syal, Rupali
• A study of learning likely data structure properties using machine learning models
  Usman, Muhammad ; Wang, Wenxi ; Wang, Kaiyuan ; Yelen, Cagdas ; Dini, Nima ; Khurshid, Sarfraz
• ASSESSING RESILIENCE OF INFRASTRUCTURES TOWARDS EXOGENOUS EVENTS BY USING PS-INSAR-BASED SURFACE MOTION ESTIMATES AND MACHINE LEARNING REGRESSION TECHNIQUES
  Fiorentini, N. ; Maboudi, M. ; Losa, M. ; Gerke, M.
• Sentiment analysis and machine learning in finance: a comparison of methods and models on one million messages
  Renault, Thomas
• Machine learning for multiple yield curve markets: fast calibration in the Gaussian affine framework
  Gümbel, Sandrine ; Schmidt, Thorsten 2020 Universität
• Estimating the short-term and long-term wind speeds: implementing hybrid models through coupling machine learning and linear time series models
  Mehdizadeh, Saeid ; Kozekalani Sales, Ali ; Safari, Mir Jafar Sadegh
• Interpretation of machine learning models using shapley values: application to compound potency and multi-target activity predictions
  Rodríguez-Pérez, Raquel ; Bajorath, Jürgen
• Validation of machine learning models to detect amyloid pathologies across institutions
  Vizcarra, Juan C. ; Gearing, Marla ; Keiser, Michael J. ; Glass, Jonathan D. ; Dugger, Brittany N. ; Gutman, David A.
• Supervised machine learning for audio emotion recognition – Enhancing film sound design using audio features, regression models and artificial neural networks
  Cunningham, Stuart ; Ridley, Harrison ; Weinel, Jonathan ; Picking, Richard
• Learn TensorFlow 2.0 – Implement Machine Learning and Deep Learning Models with Python
  2020 Apress
• Calibration of probability predictions from machine-learning and statistical models
  Dormann, Carsten F. 2020 Universität
• A Beginners Guide for Machine Learning Models with Python Environment
  Mary, X. Anitha ; Evangeline, C. Suganthi ; Munnangi, Manikanta Reddy 2020 LAP LAMBERT Academic Publishing
• Overview of existing approaches for the interpretation of machine learning models
  Cinar, Akif 2019 Hochschule Esslingen
• Absorption of Hydrocarbons on Palladium Catalysts: From Simple Models Towards Machine Learning Analysis of X-ray Absorption Spectroscopy Data
  Usoltsev, Oleg A. ; Bugaev, Aram L. ; Guda, Alexander A. ; Guda, Sergey A. ; Soldatov, Alexander V.