Sentence examples for a wide range of classification from inspiring English sources

The phrase "a wide range of classification" is correct and usable in written English.
It can be used when discussing various categories or types within a particular subject or field.
Example: "The study presents a wide range of classification for different species of plants based on their characteristics."
Alternatives: "a broad spectrum of classification" or "a diverse array of classification".

Exact(8)

A wide range of classification methods have been used for the early detection of financial risks in recent years.

Multi-layer Perceptron (MLP) with back-propagation learning can solve a wide range of classification and estimation problems.

The new expression is compared with some existing classification models with respect to their predictive value for a wide range of classification data.

The proposed system was assessed on our database of 112 DCE-MRI studies including solid breast masses, using a wide range of classification measures.

Geometric AICs have been successfully used in a wide range of classification schemes involving non-disjoint models [32, 33].

We observed a wide range of classification accuracy i.e, 49 97% on different classifiers using various feature selection methods on Lymphoma dataset.

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Similar(52)

A wider range of classifications allowed for more precise estimates using our statistical model described below because it improved the within group homogeneity of subjects within each BMI classification.

Using a LSTM network has been demonstrated to be effective for a wide range of text classification tasks, including sentiment, and can outperform traditional learners such as SVM [10].

Since the industry covers such a wide range of industrial classifications, an analysis at the four-digit SIC level is insufficient.

Random Forest is widely used across a wide range of fields for classification and regression, and its bias and error characteristics are well understood [23, 24].

Random Forest is widely used across a wide range of fields for classification and regression, and its bias and error characteristics are well understood [ 23, 24].

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