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Automated decision-making involves using data as input to be analyzed within a process, model, or algorithm or for learning and generating new models. [7] ADM systems may use and connect a wide range of data types and sources depending on the goals and contexts of the system, for example, sensor data for self-driving cars and robotics, identity data for security systems, demographic and ...
Machine Learning is becoming a useful tool to investigate and predict evacuation decision making in large scale and small scale disasters. Different solutions have been tested to predict if and when householders decide to evacuate during wildfires and hurricanes.
Decision intelligence can also be thought of as a framework that brings advanced analytics and machine learning techniques to the desktop of the non-expert decision maker, as well as incorporating, and then extending, data science to overcome the problems articulated in black swan theory.
This addresses users' requirement to assess safety and scrutinize the automated decision making in applications. [5] XAI counters the "black box" tendency of machine learning, where even the AI's designers cannot explain why it arrived at a specific decision. [6] [7]
Decision tree learning is a supervised learning approach used in statistics, data mining and machine learning.In this formalism, a classification or regression decision tree is used as a predictive model to draw conclusions about a set of observations.
Machine learning (ML) is a subfield of artificial intelligence within computer science that evolved from the study of pattern recognition and computational learning theory. [1] In 1959, Arthur Samuel defined machine learning as a "field of study that gives computers the ability to learn without being explicitly programmed". [ 2 ]
Predictive analytics statistical techniques include data modeling, machine learning, AI, deep learning algorithms and data mining. Often the unknown event of interest is in the future, but predictive analytics can be applied to any type of unknown whether it be in the past, present or future.
Deep learning is a form of machine learning that utilizes a neural network to transform a set of inputs into a ... In many practical decision-making problems, the ...
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