Robust Text Classification under Confounding Shift

نویسندگان
چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Robust Text Classification in the Presence of Confounding Bias

As text classifiers become increasingly used in real-time applications, it is critical to consider not only their accuracy but also their robustness to changes in the data distribution. In this paper, we consider the case where there is a confounding variable Z that influences both the text features X and the class variable Y . For example, a classifier trained to predict the health status of a...

متن کامل

Social Media Text Classification under Negative Covariate Shift

In a typical social media content analysis task, the user is interested in analyzing posts of a particular topic. Identifying such posts is often formulated as a classification problem. However, this problem is challenging. One key issue is covariate shift. That is, the training data is not fully representative of the test data. We observed that the covariate shift mainly occurs in the negative...

متن کامل

Robust Supervised Learning under Distribution Shift Uncertainty

Distributionally Robust Supervised Learning (DRSL) is necessary for building reliable machine learning systems. When machine learning is deployed in the real world, its performance can be significantly degraded because test data may follow a different distribution from training data. Previous DRSL minimizes the loss for the worst-case test distribution. However, our theoretical analyses show th...

متن کامل

A Robust Learning Approach for Text Classification

Previous learning approaches often assume that every part of a positive training document of a class is relevant to that class. However, in practice, it is often the case that only one or a few parts in the training document are really relevant to the class. To overcome this limitation, we propose another learning approach based on relevance-based topic model, an extension of well-known Latent ...

متن کامل

A Robust Model for Intelligent Text Classification

Methods for taking into account linguistic content into text retrieval are receiving a growing attention [16],[14]. Text categorization is an interesting area for evaluating and quantifying the impact of linguistic information. Works in text retrieval through Internet suggest that embedding linguistic information at a suitable level within traditional quantitative approaches (e.g. sense distinc...

متن کامل

ذخیره 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: Journal of Artificial Intelligence Research

سال: 2018

ISSN: 1076-9757

DOI: 10.1613/jair.1.11248