Robust weighted kernel logistic regression in imbalanced and rare events data
نویسندگان
چکیده
منابع مشابه
Robust weighted kernel logistic regression in imbalanced and rare events data
Recent developments in computing and technology, along with the availability of large amounts of raw data, have contributed to the creation of many effective techniques and algorithms in the fields of pattern recognition and machine learning. The main objectives for developing these algorithms include identifying patterns within the available data or making predictions, or both. Great success h...
متن کاملWeighted logistic regression for large-scale imbalanced and rare events data
Latest developments in computing and technology, along with the availability of large amounts of raw data, have led to the development of many computational techniques and algorithms. Concerning binary data classification in particular, analysis of data containing rare events or disproportionate class distributions poses a great challenge to industry and to the machine learning community. Logis...
متن کاملLogistic Regression in Rare Events Data 1
Rare events are binary dependent variables with dozens to thousands of times fewer ones (events, such as wars, vetoes, cases of political activism, or epidemiological infections) than zeros (\nonevents"). In many literatures, rare events have proven di cult to explain and predict, a problem that seems to have at least two sources. First, popular statistical procedures, such as logistic regressi...
متن کاملLogistic Regression in Rare Events Data
We study rare events data, binary dependent variables with dozens to thousands of times fewer ones (events, such as wars, vetoes, cases of political activism, or epidemiological infections) than zeros (“nonevents”). In many literatures, these variables have proven difficult to explain and predict, a problem that seems to have at least two sources. First, popular statistical procedures, such as ...
متن کاملInfinitely Imbalanced Logistic Regression
In binary classification problems it is common for the two classes to be imbalanced: one case is very rare compared to the other. In this paper we consider the infinitely imbalanced case where one class has a finite sample size and the other class’s sample size grows without bound. For logistic regression, the infinitely imbalanced case often has a useful solution. Under mild conditions, the in...
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: Computational Statistics & Data Analysis
سال: 2011
ISSN: 0167-9473
DOI: 10.1016/j.csda.2010.06.014