Examples of using Predictive data in English and their translations into Indonesian
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How to find the right predictive data. .
Some forms of Predictive Data Mining generate rules that are the requirements to get a result.
Yet today, companies also expect to have access to predictive data.
For example, the results of predictive data mining can be added as custom measures to a cube.
Some forms of predictive data mining generate rules, which are conditions that imply a given outcome.
Huisstede revealed that the registryis also experimenting with artificial intelligence(AI) for predictive data systems.
Its predictive data entry can detect patterns and extract and enter data that follows a recognizable pattern.
Today's startup founders have access to awide range of tools that offer historical and predictive data analyses to spur better decision making.
The researchers found that the most predictive data sets were traditional surveillance sources collected from across the U.S. by the CDC.
The algorithm has a capability that is known as auto-tuning capability, with the help of which it derives or extracts insights or values from raw data such as age or gender, and after that,it can create predictive data models.
With content, social and predictive data at the core, we have built a model that merges all of the various media sources and essentially redefines the PR capability entirely.”.
Google's, Amazon's and Facebook's“surveillance capitalism,” as author Shoshana Zuboff has argued,also uses predictive data to“tune and herd our behavior toward the most profitable outcomes.”.
The ability to make a small scale model of a ship, and extract useful predictive data with respect to a full size ship, depends directly on the experimentalist applying Reynolds' turbulence principles to friction drag computations, along with a proper application of William Froude's theories of gravity wave energy and propagation.
The two basic data mining tasks are: descriptive data mining tasks whichhelp to understand the characteristic properties of dataset and predictive data mining tasks which are used to perform predictions based on available dataset.
The goal of data mining is prediction, and predictive data mining is the most common type of data mining with the most direct business applications.
As Grab develops its products, it leverages a model of distributed engineering teams to access specific sets of expertise in each of its R&D centres around the world,such as machine learning, predictive data analytics, mobile-first technology, and consumer-focused user experience.
The ultimate goal of data mining is prediction and predictive data mining is the most common type and the one that has the most direct business applications.
The kinds of patterns that can be discovered depend upon the data mining tasks given. two types of data mining tasks are there descriptive data mining tasks thatdescribe the general properties of the existing data, and predictive data mining tasks that attempt to do predictions based on inference on available data. data mining process.
It is generally an area of data scientist anddata analysts who build predictive data models using the advanced algorithm, regression analysis, time series analysis, decision tree.
There are two types of data mining tasks: descriptive data mining tasks thatdescribe the general properties of the existing data, and predictive data mining tasks that attempt to do predictions based on inference on available data. .
It is generally an area of data of scientists anddata analysts who construct predictive data models using advanced algorithms, regression analysis, time series analysis, decision trees.
Charts with historical and predictive market data.
This is a key area ofextension into the fast growing Data Science, Predictive Analytics and Big Data arenas.
They have built a predictive model using data on previous employees who have left the organisation.
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