Sentence examples for sparse data points from inspiring English sources

While the scattered data points are the sparse data points in the outside layer of a cluster.

Unfortunately, the prediction accuracy is rather low, which might be due to the sparse data points in the high-dimensional feature space.

Interpretation is required to interpolate between sparse field data points using ambiguous geophysical data in covered terranes.

This suggests that the data generation process may be misled by the sparse distribution of data points.

The table in previous versions of the Standards of Medical Care in Diabetes describing the correlation between A1C and mean glucose was derived from relatively sparse data (one 7-point profile over 1 day per A1C reading) in the primarily Caucasian type 1 diabetic participants in the DCCT (52).

In previous versions of the Standards of Medical Care in Diabetes, the table describing the correlation between A1C and mean glucose was derived from relatively sparse data (one seven-point profile over 1 day per A1C reading) in the primarily Caucasian type 1 participants in the DCCT (50).

The table in previous versions of the Standards of Medical Care in Diabetes describing the correlation between A1C and mean glucose was derived from relatively sparse data (one seven-point profile over 1 day per A1C reading) in the primarily Caucasian type 1 participants in the Diabetes Control and Complications Trial (DCCT) trial (43).

The table in pre-2009 versiofs of the "Standards of Medical Care in Diabetes" describing the correlation between A1C and mean glucose was derived from relatively sparse data (one 7-point profile over 1 day per A1C reading) in the primarily Caucasian type 1 participants in the DCCT (68).

In high dimensional space, data points become sparse making the use of some distance measures meaningless.

The choice of the ε-insensitive loss function hence induces a sparse solution that only depends on data points with non-zero loss, which are called 'support vectors' [27].

In this paper, semi-supervised double sparse graphs (sDSG) based dimensionality reduction is proposed, which considers both the positive and negative structure relationship of data points by using double sparse graphs.