منابع مشابه
Linear Probability Forecasting
Multi-class classification is one of the most important tasks in machine learning. In this paper we consider two online multi-class classification problems: classification by a linear model and by a kernelized model. The quality of predictions is measured by the Brier loss function. We suggest two computationally efficient algorithms to work with these problems and prove theoretical guarantees ...
متن کاملEvaluating the capabilities of Logistic Model Tree in predicting the occurrence probability of daily precipitation
Due to the location of Iran in arid and semi-arid regions and the inhomogeneous distribution of precipitation, predicting the occurrence of precipitation is important, therefore, researchers are implementing novel methods to identify and predict this parameter accurately. Thus the purpose of the current study is to investigate the capabilities of Logistic Model Tree (LMT) in predicting the occu...
متن کاملSelf-calibrating Probability Forecasting
In the problem of probability forecasting the learner’s goal is to output, given a training set and a new object, a suitable probability measure on the possible values of the new object’s label. An on-line algorithm for probability forecasting is said to be well-calibrated if the probabilities it outputs agree with the observed frequencies. We give a natural nonasymptotic formalization of the n...
متن کاملA Generalized Study of Precipitation Forecasting
Proceeding on a purely physical basis, Thompson and Collins employed in their pilot study observed winds to compute divergence over a triangular area in the Midwest. From this divergence vertical motion was then derived using continuity considerations and, with observed moisture, was used to compute the average rate of precipitation over the area. Their procedure was completely numerical and d...
متن کاملUncertainty Analysis of Magnitude, Temporal and Spatial Distribution of Precipitation in Flood Forecasting
عدم قطعیت در بارش پیش بینی شده، یک منبع اصلی عدم قطعیت در پیش بینی بهنگام سیل می باشد. عدم قطعیت بارش از عدم قطعیت در مقدار بارش، توزیع زمانی و توزیع مکانی بارش تشکیل می شود. در این تحقیق به منظور پخش عدم قطعیت بارش در مدل پیش بینی سیل HEC-1 ، روش گسسته سازی زمانی در چهارچوب اصل بسط تئوری فازی و در ترکیب با الگوریتم ژنتیک نرمال بکار برده می شود. عدم قطعیت به علت توزیع زمانی ناشناخته بارش با ت...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Monthly Weather Review
سال: 1920
ISSN: 0027-0644,1520-0493
DOI: 10.1175/1520-0493(1920)48<645:fpipop>2.0.co;2