Abstract: In an approach for optimizing abnormal point detection, a processor receives a set of data, wherein the set of data is partially labeled time series data; determines a data block size for the set of data; splits the set of data into data blocks based on the data block size; computes trait measurements for traits for each data block; assigns a tag to each data block, wherein the tag is selected from the group consisting of a normal tag, an abnormality tag, and an unknown tag; uses the respective data blocks with either the normal tag or the abnormality tag as training data; updates the training data with artificial abnormalities; trains a detection model with the updated training data; and utilizes the trained detection model to predict whether the respective data blocks with the unknown tag have an abnormality or no abnormality.

Abstract: An embodiment identifies, by a post-modeling category merging engine, a plurality of valid pairs associated with a categorical predictor, the plurality of valid pairs representing potential mergers of categories associated with a categorical predictor of a predictive model. The embodiment tests, by the post-modeling category merging engine, a merge strategy for the plurality of valid pairs to determine a merger that minimizes a loss in accuracy of the predictive model. The embodiment merges, by the post-modeling category merging engine based on the testing, a valid pair in the plurality of valid pairs to form a hybrid category.

Abstract: A time series anomaly detection method, system, and computer program product that processes time series data includes absorbing profiles of the time series data and anomaly types of a model as features, optimizing biased ranks to create optimized ranks through merging initial ranks with new ranks generated by real anomalies, and auto-suggesting the optimized ranks for saving a predetermined amount of data operation.

Abstract: A method, computer system, and a computer program product are provided for post-modeling feature evaluation. In one embodiment, at least at least one post model visual output and associated data is obtained that at least includes an individual conditional expectation (ICE) plot and a partial dependence (PDP) plot. Using the associated data and the plots, a Feature Importance (PI) plot is provided. A plurality of features is then determined for each PI, PDP and ICE plots to calculate at least one Interesting Value for each plot. An overall score is also calculated for each plurality of features based on the associated Interesting Values for each PDP, ICE and PI plots. At least one top feature is selected based on said scores. A final plot is then generated at least reflecting the top feature. The final plot combines the PI, PDP and ICE plots together.

Abstract: Disclosed are a computer-implemented method, a system and a computer program product for model exploration. Model feature importance of each model of a plurality of models can be obtained, the plurality of models can be grouped into a plurality of model clusters based on the model feature importance of each model, and the model feature importance can be presented by box-plot or confidence interval.

Abstract: In an approach, a processor selects a top N features for a machine learning (ML) model; discretizes values of each continuous feature of the top N features; generates a set of combination values that each represent a unique combination of feature values in for a data record; predicts, using the ML model, a target value for each record generating predicted target values; groups the predicted target values based on the combination value for each respective record; fits a distribution for each grouping of the predicted target values associated with a respective combination value generating a set of distributions; clusters and refits the set of distributions using a clustering algorithm resulting in a set of clusters and a refitted distribution for each cluster of the set of clusters; and outputs a visualization of the refitted distribution for each cluster as a distribution curve on a graph along with the associated records.

Abstract: A softening resistant copper alloy, a preparation method, and an application thereof, the softening-resistant copper alloy, comprising 0.1%-1.0 wt % Cr, 0.01%-0.2 wt % Zr, 0.01%-0.10 wt % Si, and ?0.10 wt % Fe, and with the remaining of copper and inevitable impurities, wherein the microstructure of the copper alloy contains comprises: an elemental Cr phase, a Cu5Zr phase, and a Cr3Si phase. In the copper alloy of the present invention, the high-temperature softening resistance effect of the material is improved by adding a proper amount of Si to form a compound Cr3Si, and the strength and the high-temperature softening resistance of the material are further improved by strengthening the copper alloy matrix by the elemental Cr phase and the Cu5Zr phase, using the synergistic effect of the Cr3Si phase and the elemental Cr phase and by controlling the content of the impurity Fe. The copper alloy can be applied to contact lines and welding materials to prolong the service life of the materials.

Abstract: The present invention provides methods to identify ISG15 target proteins, methods to identify compounds that alter the conjugation of ISG15 with target proteins, methods for altering the level of ISG15-conjugated protein in a patient or a sample, methods to diagnose a patient having a malcondition characterized by an altered level of ISG15-conjugated protein, ISG15-conjugates, methods to treat cancer by promoting conjugation of a target protein to ISG15, and antibodies that selectively bind to ISG15-conjugates.

Abstract: The present invention is directed to identification of agents that modulate UBP43 activity as well as associated methods, uses, processes, compositions and agents. In particular, the invention is directed to in vivo and in vitro methods to identify an agent that inhibits or stimulates UBP43 activity within a cell, a method for inducing cellular apoptosis, a method for affecting cellular reaction to interferon, a method for treating disease associated with cellular proliferation by causing apoptosis, and a method for treating both acute and chronic diseases in which interferon exerts a beneficial effect. The invention is also directed to modified ISG15-conjugates that have lowered or no susceptibility to UBP43 cleavage, pharmaceutical compositions of the agents, conjugates, and additional modified ISG15-conjugates.