prediction of anomalies by vs prediction of anomalies from

Both phrases are correct, but they are used in slightly different contexts. 'Prediction of anomalies by' is used when referring to the method or entity making the prediction, while 'prediction of anomalies from' is used when referring to the source or data used for the prediction.

Last updated: March 19, 2024 • 434 views

prediction of anomalies by

This phrase is correct and commonly used in English.

This phrase is used when referring to the method or entity that is making the prediction of anomalies.

Examples:

The prediction of anomalies by the machine learning algorithm was accurate.
The prediction of anomalies by the expert analyst was based on historical data.

Show examples from the web [+]

CONTENTS. 1. Introduction. 1. 2. Mean Free-Air Gravity Anomalies. 4. 3. Prediction of Anomalies by Trend Removal. 7. 4. The b-const. - Problem and Isostasy.
Because of the risk for anomalies is primarily determined by the HbA1c value, efficiency of first-trimester prediction of anomalies by NT is only effective in women ...
Anomaly Detection in Co-evolving Data Streams Friday, October 24, 2014. Jing He, PhD. College of Engineering and Science Victoria University, Australia
2014年4月15日 ... It includes the detection/prediction of anomalies by analyzing differences, changes, and trends in correlated multiple data streams.

Alternatives:

detection of anomalies by
identification of anomalies by
forecasting anomalies by
anticipation of anomalies by
recognition of anomalies by

prediction of anomalies from

This phrase is correct and commonly used in English.

This phrase is used when referring to the source or data from which the prediction of anomalies is made.

Examples:

The prediction of anomalies from the sensor data was reliable.
The prediction of anomalies from historical patterns helped prevent system failures.

Show examples from the web [+]

consists of prediction of anomalies from simulation or experimental data, given a priori knowledge of the underlying model parameters. In the absence of a.

Alternatives:

detection of anomalies from
identification of anomalies from
forecasting anomalies from
anticipation of anomalies from
recognition of anomalies from

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prediction of anomalies by vs prediction of anomalies from