Automated adaptive data analysis using dynamic data quality assessment

1. An apparatus for automated adaptive data analysis, the apparatus comprising at least one processor and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to:

generate, using a predictive model, a judgment associated with a new data sample having a particular data type, wherein the new data sample is collected from a data stream, the judgment generated based on a feature vector associated with the new data sample, wherein the feature vector represents an optimal view of the new data sample;

determine whether to add the new data sample and the judgment to a reservoir of data samples in response to receiving a data quality estimate for the new data sample from an oracle, the reservoir of data samples identified based at least in part on the particular data type, the reservoir of data samples associated with reservoir summary statistics, wherein the determination is based on one of whether the new data sample statistically belongs in the data reservoir or whether the judgment is associated with a high confidence value; and

in an instance in which the new data sample and its judgment are added to the reservoir of data, update the reservoir summary statistics.

2. The apparatus of claim 1 , wherein the predictive model is adapted using a set of training data samples having the particular data type.

3. The apparatus of claim 2 , wherein the at least one memory and the computer program code configured to, with the at least one processor, further cause the apparatus to:

compare the reservoir summary statistics to training data summary statistics derived from the set of training data samples having the particular data type.

4. The apparatus of claim 3 , wherein the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to:

determine, based in part on the comparing, whether to update the set of training data samples.

5. The apparatus of claim 1 , wherein the judgment includes a confidence value.

6. The apparatus of claim 1 , wherein the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to:

determine whether the new data sample statistically belongs in the reservoir.

7. The apparatus of claim 1 , wherein the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to:

determine whether the judgment and a second judgment generated by and received from the oracle match, the second judgment associated with the new data sample.

8. The apparatus of claim 7 , wherein the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to:

in an instance in which the judgment and the second judgment do not match, replace the judgment with the second judgment.

9. A system, comprising: one or more computers and one or more storage devices, the one or more computers each comprising a processor, the one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to:

generate, using a predictive model, a judgment associated with a new data sample having a particular data type wherein the new data sample is collected from a data stream, the judgment generated based on a feature vector associated with the new data sample, wherein the feature vector represents an optimal view of the new data sample;

determine whether to add the new data sample and the judgment to a reservoir of data samples in response to receiving a data quality estimate for the new data sample from an oracle, the reservoir of data samples identified based at least in part on the particular data type, the reservoir of data samples associated with reservoir summary statistics, wherein the determination is based on one of whether the new data sample statistically belongs in the data reservoir or whether the judgment is associated with a high confidence value; and

in an instance in which the new data sample and its judgment are added to the reservoir of data, update the reservoir summary statistics.

10. The system of claim 9 , wherein the predictive model is adapted using a set of training data samples having the particular data type.

11. The apparatus of claim 10 , wherein the instructions are operable, when executed by the one or more computers, to further cause the one or more computers to:

compare the reservoir summary statistics to training data summary statistics derived from the set of training data samples having the particular data type.

12. The system of claim 11 , wherein the instructions are operable, when executed by the one or more computers, to further cause the one or more computers to:

determine, based in part on the comparing, whether to update the set of training data samples.

13. The system of claim 9 , wherein the judgment includes a confidence value.

14. The system of claim 9 , wherein the instructions are operable, when executed by the one or more computers, to further cause the one or more computers to:

determine whether the new data sample statistically belongs in the reservoir.

15. The system of claim 9 wherein the instructions are operable, when executed by the one or more computers, to further cause the one or more computers to:

determine whether the judgment and a second judgment generated by and received from the oracle match, the second judgment associated with the new data sample.

16. The system of claim 15 , wherein the instructions are operable, when executed by the one or more computers, to further cause the one or more computers to:

in an instance in which the judgment and the second judgment do not match, replace the judgment with the second judgment.