Sentence examples for sensitive learning from inspiring English sources

Minimal cost decision tree construction plays a crucial role in cost sensitive learning.

His conclusion: Technology can make phones not just smart but sensitive, learning things we didn't know about ourselves.

Experiments also show that CSA helps dimension sensitive learning algorithms such as k-nearest neighbor (kNN) to eliminate the "Curse of Dimensionality" and as a result reaches a comparable performance with support vector machine (SVM) in text categorization applications.

While it is a challenge to construct many suitable transformation functions for the costs with diverse units, this paper designs a heterogeneous-cost sensitive learning (HCSL) algorithm to make split attribute selection more effective.

In cost sensitive learning, misclassification of the marginal class is assigned a high cost which the algorithm then attempts to lessen.

The imbalanced UCI Machine Learning Repository datasets are used in many standard cost sensitive learning papers in literature [2, 3, 10].

As an example of the sensitivity that can be achieved with the sampling methods and cost-sensitive learning while maintaining a reasonable specificity, Table  9 shows the performance of the classifiers with the highest sensitivity and a specificity of at least 0.5.

These techniques have been traditionally proposed under three different perspectives: data treatment, adaptation of algorithms, and cost-sensitive learning.

A survey of cost-sensitive learning techniques over the years is covered in [1].

We use two approaches to deal with the imbalance problem: sampling methods and cost-sensitive learning.

We used sampling and cost-sensitive learning approaches to improve the sensitivity of our classifiers by dealing with this imbalance.