"too few points" is grammatically correct and can be used in written English.
It is often used to indicate that there are not enough important or relevant pieces of information or evidence being presented. Example: The argument presented by the defense lawyer was weak and had too few points to convince the jury.
Those problems add up to too few points for the Giants to make up the difference.
The Bills are averaging 328.5 yards per game but have too few points to show for it.
"We have come to the view that we have too few points at the end of the day," said the sporting director, Detlev Dammeier.
In late September, Douglas R. King, the chief executive of the Museum of Flight in Seattle, met with NASA officials to argue that evaluators gave his museum too few points for its annual attendance and the number of foreign visitors to the city and gave the Intrepid too much credit for its readiness to accept a shuttle.
"We have come to the view that we have too few points at the end of the day," said the sporting director, Detlev Dammeier, after Bielefeld were hammered 6-0 by Dortmund, leaving the club third-bottom: the relegation play-off spot.
Issues included insufficient numbers of animals per group per time point, too few time points, use of pooled tissue samples, and lack of QC metrics (e.g., demonstration of RNA purity).
However, there were too few data points in the earliest time period in the Asian and Black groups to show after smoothing.
These mass filters prevent monitoring of multiple fragments in multiple-reaction monitoring (MRM -type experiMRM -typed thus prexperimentstificandon, or cause thusfew data precludeo be obtaidentificationpeak, and thus preclude quantitatior.
As kinases with too few data points are omitted, this tree therefore significantly improves upon previous analyses that also included rather unreliable data points.
A common pitfall in machine learning analysis that occurs when a complex model is trained on too few data points and becomes specific to the training data, resulting in poor performance on other data.
