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 8):
A method comprising:\n accessing, from a non-transitory computer-readable medium, (i) a machine-learning model that transforms input attribute values into a predictive or analytical output value for an entity associated with the input attribute values and (ii) training data for training the machine-learning model, wherein the training data is grouped into attributes; selecting, by a processing device, a subset of attributes from the attributes of the training data; transforming, by the processing device, the subset of attributes into a transformed attribute by performing operations comprising:\n grouping portions of the training data for the subset of attributes into respective multi-dimensional bins, wherein each dimension for the multi-dimension bins corresponds to a respective one of the attributes in the subset of attributes, \n computing interim predictive output values, wherein each interim predictive output value is generated from a respective training data portion in a respective one of the multi-dimensional bins, \n computing smoothed interim output values by applying a smoothing function to the interim predictive output values, and \n outputting the smoothed interim output values as a dataset for the transformed attribute; and \n training, by the processing device, the machine-learning model with the transformed attribute.

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): 0.3624639595117836
- 35 USC 102 Novelty (BERT): 0.4780281640805413
- Combined Prediction Score: 0.3740203799686594
- Mean Citation Score: 183.623624
- Max Citation Score: 207.1118
- Similarity Product: 157.88606855516431

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