PATENT CLAIM ANALYSIS

Application Number: 16334190
Application Type: Utility
Filing Date: 2019-03
Publication Date: 2019-07
Patent Classification: ["706", "012000"]

Abstract:
In some aspects, a machine-learning model, which can transform input attribute values into a predictive or analytical output value, can be trained with training data grouped into attributes. A subset of the attributes can be selected and transformed into a transformed attribute used for training the model. The transformation can involve grouping portions of the training data for the subset of attributes into respective multi-dimensional bins. Each dimension of a multi-dimensional bin can correspond to a respective selected attribute. The transformation can also involve computing interim predictive output values. Each interim predictive output value can be generated from a respective training data portion in a respective multi-dimensional bin. The transformation can also involve computing smoothed interim output values by applying a smoothing function to the interim predictive output values. The transformation can also involve outputting the smoothed interim output values as a dataset for the transformed attribute.

Claim (Index 18):
The non-transitory computer-readable medium of  claim 15 , wherein the instructions, when executed the processing device, cause the processing device to select the subset of attributes by performing operations comprising, for a particular attribute from the subset of attributes:\n retrieving, from the training data, data samples including values for the particular attribute and corresponding values for a response variable; computing a correlation between the data samples having the values for the particular attribute and the corresponding values for the response variable; and including the particular attribute in the subset of attributes based on the correlation exceeding a threshold correlation indicative of monotonicity between the particular attribute and the response variable.

Metadata:
- Claim Count in Document: 27.0
- Percentile: 99.0
- Lexical Diversity: 2.46875
- Patent Class: 706.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['16340256', '15750363', '14935426', '14562541', '14672749']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3622870615465731
- 35 USC 102 Novelty (BERT): 0.4787990280871096
- Combined Prediction Score: 0.3739382582006268
- Mean Citation Score: 183.623624
- Max Citation Score: 207.1118
- Similarity Product: 156.63673520358802

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 0
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test