A brief history of AI: how to prevent another winter (a critical review)
Artificial intelligence (AI) technology is sweeping the globe, leading to bold statements by
notable figures:“[AI] is going to change the world more than anything in the history of …
notable figures:“[AI] is going to change the world more than anything in the history of …
The simplicity principle in perception and cognition
J Feldman - Wiley Interdisciplinary Reviews: Cognitive Science, 2016 - Wiley Online Library
The simplicity principle, traditionally referred to as Occam's razor, is the idea that simpler
explanations of observations should be preferred to more complex ones. In recent decades …
explanations of observations should be preferred to more complex ones. In recent decades …
Very simple classification rules perform well on most commonly used datasets
RC Holte - Machine learning, 1993 - Springer
This article reports an empirical investigation of the accuracy of rules that classify examples
on the basis of a single attribute. On most datasets studied, the best of these very simple …
on the basis of a single attribute. On most datasets studied, the best of these very simple …
The CN2 induction algorithm
P Clark, T Niblett - Machine learning, 1989 - Springer
Abstract Systems for inducing concept descriptions from examples are valuable tools for
assisting in the task of knowledge acquisition for expert systems. This paper presents a …
assisting in the task of knowledge acquisition for expert systems. This paper presents a …
ARTMAP: Supervised real-time learning and classification of nonstationary data by a self-organizing neural network
This 1991 article introduces ARTMAP, an ART architecture for supervised learning. The ART
1, ART 2, and ART 3 networks were designed to learn and perform pattern recognition tasks …
1, ART 2, and ART 3 networks were designed to learn and perform pattern recognition tasks …
Models of incremental concept formation
Given a set of observations, humans acquire concepts that organize those observations and
use them in classifying future experiences. This type of concept formation can occur in the …
use them in classifying future experiences. This type of concept formation can occur in the …
Sequential covering rule induction algorithm for variable consistency rough set approaches
We present a general rule induction algorithm based on sequential covering, suitable for
variable consistency rough set approaches. This algorithm, called VC-DomLEM, can be …
variable consistency rough set approaches. This algorithm, called VC-DomLEM, can be …
Algorithms for approximate minimization of the difference between submodular functions, with applications
We extend the work of Narasimhan and Bilmes [30] for minimizing set functions
representable as a difference between submodular functions. Similar to [30], our new …
representable as a difference between submodular functions. Similar to [30], our new …
Multiple comparisons in induction algorithms
A single mechanism is responsible for three pathologies of induction algorithms: attribute
selection errors, overfitting, and oversearching. In each pathology, induction algorithms …
selection errors, overfitting, and oversearching. In each pathology, induction algorithms …
Selecting examples for partial memory learning
MA Maloof, RS Michalski - Machine Learning, 2000 - Springer
This paper describes a method for selecting training examples for a partial memory learning
system. The method selects extreme examples that lie at the boundaries of concept …
system. The method selects extreme examples that lie at the boundaries of concept …