Definition of datapoint in US English:

datapoint

nounˈdatəˌpointˈdātə-

An identifiable element in a data set.
software that can quickly process tens of thousands of datapoints
Example sentencesExamples
- The slopes were evaluated from the tangents of the linear fit for all the datapoints between two points i and i + NP - 1 (NP = number of datapoints over the distance D) for all the points i in the height profile.
- Simply removing either the last two groups or the four datapoints with the highest acceptor levels results in a reduced value of p = 0.2454, indicating a lack of evidence of dependence.
- Support vector machines can be phrased as statistical query algorithms, but the number of queries scales with the number of datapoints.
- Dividing the data into six groups of ~ 25 datapoints, with increasing uD + A, shows a greater level of heterogeneity in the local density s-values while maintaining a strong negative dependence of s on uD + A.
- The whole set of 40 datapoints allows us to determine a good average of k 0 and [beta]. Only for the tryptophans of NSCP is an additional lifetime found, which might be an indication for additional sources of heterogeneity.

Definition of datapoint in US English:

datapoint

nounˈdātə-

An identifiable element in a data set.
software that can quickly process tens of thousands of datapoints
Example sentencesExamples
- The whole set of 40 datapoints allows us to determine a good average of k 0 and [beta]. Only for the tryptophans of NSCP is an additional lifetime found, which might be an indication for additional sources of heterogeneity.
- Support vector machines can be phrased as statistical query algorithms, but the number of queries scales with the number of datapoints.
- The slopes were evaluated from the tangents of the linear fit for all the datapoints between two points i and i + NP - 1 (NP = number of datapoints over the distance D) for all the points i in the height profile.
- Simply removing either the last two groups or the four datapoints with the highest acceptor levels results in a reduced value of p = 0.2454, indicating a lack of evidence of dependence.
- Dividing the data into six groups of ~ 25 datapoints, with increasing uD + A, shows a greater level of heterogeneity in the local density s-values while maintaining a strong negative dependence of s on uD + A.

单词	datapoint
释义	Definition of datapoint in US English: datapoint nounˈdatəˌpointˈdātə- An identifiable element in a data set. software that can quickly process tens of thousands of datapoints Example sentencesExamples The slopes were evaluated from the tangents of the linear fit for all the datapoints between two points i and i + NP - 1 (NP = number of datapoints over the distance D) for all the points i in the height profile. Simply removing either the last two groups or the four datapoints with the highest acceptor levels results in a reduced value of p = 0.2454, indicating a lack of evidence of dependence. Support vector machines can be phrased as statistical query algorithms, but the number of queries scales with the number of datapoints. Dividing the data into six groups of ~ 25 datapoints, with increasing uD + A, shows a greater level of heterogeneity in the local density s-values while maintaining a strong negative dependence of s on uD + A. The whole set of 40 datapoints allows us to determine a good average of k 0 and [beta]. Only for the tryptophans of NSCP is an additional lifetime found, which might be an indication for additional sources of heterogeneity. Definition of datapoint in US English: datapoint nounˈdātə- An identifiable element in a data set. software that can quickly process tens of thousands of datapoints Example sentencesExamples The whole set of 40 datapoints allows us to determine a good average of k 0 and [beta]. Only for the tryptophans of NSCP is an additional lifetime found, which might be an indication for additional sources of heterogeneity. Support vector machines can be phrased as statistical query algorithms, but the number of queries scales with the number of datapoints. The slopes were evaluated from the tangents of the linear fit for all the datapoints between two points i and i + NP - 1 (NP = number of datapoints over the distance D) for all the points i in the height profile. Simply removing either the last two groups or the four datapoints with the highest acceptor levels results in a reduced value of p = 0.2454, indicating a lack of evidence of dependence. Dividing the data into six groups of ~ 25 datapoints, with increasing uD + A, shows a greater level of heterogeneity in the local density s-values while maintaining a strong negative dependence of s on uD + A.
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