Modeling reverse thinking for machine learning
نویسندگان
چکیده
منابع مشابه
Modeling reverse thinking for machine learning
Human inertial thinking schemes can be formed through learning, which are then applied to quickly solve similar problems later. However, when problems are significantly different, inertial thinking generally presents the solutions that are definitely imperfect. In such cases, people will apply creative thinking, such as reverse thinking, to solve problems. Similarly, machine learning methods al...
متن کاملMachine learning algorithms in air quality modeling
Modern studies in the field of environment science and engineering show that deterministic models struggle to capture the relationship between the concentration of atmospheric pollutants and their emission sources. The recent advances in statistical modeling based on machine learning approaches have emerged as solution to tackle these issues. It is a fact that, input variable type largely affec...
متن کاملModeling Language for Machine Learning
For a given specific problem an efficient algorithm has been the matter of study. However, an alternative approach orthogonal to this approach comes out, which is called a reduction. In general for a given specific problem this reduction approach studies how to convert an original problem into subproblems. This paper proposes a formal modeling language to support this reduction approach. We sho...
متن کاملMachine Learning Methods for Inverse Modeling
Geostatistics has become a preferred tool for the identification of lithofacies from sparse data, such as measurements of hydraulic conductivity and porosity. Recently we demonstrated that the support vector machine (SVM), a tool from machine learning, can be readily adapted for this task, and offers significant advantages. On the conceptual side, the SVM avoids the use of untestable assumption...
متن کاملMachine Learning Approaches for Modeling Spammer Behavior
Spam is commonly known as unsolicited or unwanted email messages in the Internet causing potential threat to Internet Security. Users spend a valuable amount of time deleting spam emails. More importantly, ever increasing spam emails occupy server storage space and consume network bandwidth. Keyword-based spam email filtering strategies will eventually be less successful to model spammer behavi...
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: Soft Computing
سال: 2019
ISSN: 1432-7643,1433-7479
DOI: 10.1007/s00500-019-03980-x