Sentence examples similar to classification algorithms with training data from inspiring English sources

The land use analysis was performed using a supervised classification technique based on the Gaussian maximum likelihood (GML) algorithm with training data (collected from the field using GPS).

We present an empirical comparison of classification algorithms when training data contains attribute noise levels not representative of field data.

Failure to account for correlation among observations may result in a classification algorithm overfitting the training data and producing overoptimistic estimated error rates and may make subsequent classifications unreliable.

Classification tree models had higher classification accuracy with the training data, but were less robust when used for predictions with the test data.

We validated the detection and classification algorithms by comparison with trained human operators on the same data.

The application of different classification algorithms to the collected data allowed predicting subsequent hyperbilirubinemia with high accuracy.

After training, each classification algorithm with different sets of classifiers was cross-validated with the test set.

We first performed clustering using hierarchical Ward's method, the most common classification algorithm used with neuronal data.

For example, clustering algorithms search for groups of similar records, and classification algorithms find data structures to predict the class label of a previously unseen data record according to annotated (classified) training data.

The classification algorithms were applied to the training data of each of these data sets and subsequently evaluated on the test data.

The kNN algorithm uses training data directly for classification.