Search results
Results From The WOW.Com Content Network
Predictive modeling is a statistical technique used to predict future behavior. It utilizes predictive models to analyze a relationship between a specific unit in a given sample and one or more features of the unit. The objective of these models is to assess the possibility that a unit in another sample will display the same pattern.
The use of Model Based Condition Monitoring for predictive maintenance programs is becoming increasingly popular over time. This method involves spectral analysis on the motor's current and voltage signals and then compares the measured parameters to a known and learned model of the motor to diagnose various electrical and mechanical anomalies.
Model-based voltage and current systems (MBVI systems): This is a technique that makes use of the information available from the current and voltage signals across all three phases simultaneously. Model-based systems are able to identify many of the same phenomena also seen by more conventional techniques, covering electrical, mechanical, and ...
This might include, for example: Standardized mission profile with specific fixed duration mission phases; Sources for failure rate and failure mode data; Fault detection coverage that system built-in test will realize; Whether the analysis will be functional or piece-part; Criteria to be considered (mission abort, safety, maintenance, etc.)
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
PMML provides a way for analytic applications to describe and exchange predictive models produced by data mining and machine learning algorithms. It supports common models such as logistic regression and other feedforward neural networks. Version 0.9 was published in 1998. [1] Subsequent versions have been developed by the Data Mining Group. [2]
Predictive learning is a machine learning (ML) technique where an artificial intelligence model is fed new data to develop an understanding of its environment, capabilities, and limitations. This technique finds application in many areas, including neuroscience , business , robotics , and computer vision .
For example, a large consumer organization such as a mobile telecommunications operator will have a set of predictive models for product cross-sell, product deep-sell (or upselling) and churn. It is also now more common for such an organization to have a model of savability using an uplift model. This predicts the likelihood that a customer can ...