Examples of using Classifiers in English and their translations into Japanese
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Derived Classifiers.
Classifiers- freund-turbo corporation.
Inventory list: Air Classifiers.
Spiral classifiers machine.
Add high efficiency classifiers.
Classifiers- freund-turbo corporation.
Scripts and predefined classifiers.
Extending of the classifiers for use in projects.
Style: Sinking type spiral classifiers.
Extending of the classifiers for use in user.
These abstractions can then be used by linear ornonlinear classifiers.
Decision trees are the most popular weak classifiers used in boosting schemes.
This leads to a substantial deterioration in performance of traditionally favoured classifiers.
Prior work on object detection repurposes classifiers to perform detection.
Air Sifters: Or airflow classifiers that separate and clean crumb from dust and textile fluff.
This example demonstrates howneural networks can be used as classifiers for cancer detection.
As a result, the verdicts of all classifiers are integrated, and the system produces a final verdict.
Pre-built drag-and-drop developercomponents leverage Spark machine learning classifiers in a single tool.
Many established classifiers fail to identify the minority class when it is much smaller than the majority class.
Offers packing and loading equipment, bulk conveyors, and classifiers for cement and bulk products.
Hierarchical Naive Bayes Classifiers for uncertain data(an extension of the Naive Bayes classifier).
Even though discussions tend toward philosophy, it is an important question to answer for creators andusers of anti-spam classifiers.
The full list of classifiers can be obtained by running python setup. py register--list-classifiers.
Two related variations of basic gradient descent thatare often used with logistic regression classifiers are called BFGS and L-BFGS.
Classifiers are used to categorize data, while regression models broadly deal with extrapolating out trends to make predictions.
Then, we introduce tractable proxies to design convex margin-based classifiers that satisfy these preference-based notions of fairness.
Two-class Discrete AdaBoost Algorithm: Training(steps 1 to 3) and Evaluation(step 4) NOTE: As well as the classical boosting methods,the current implementation supports 2-class classifiers only.
Most machine learning systems, including statistical text classifiers like Naive Bayes, are unable to automatically identify contested documents.
It outputs a list of natural language classifiers made by the Create and train a classifier BLOCK to the logs section(see example below).
Devote more engineering resources to apply the most advancedmachine learning research to train new“content classifiers” to help more quickly identify and remove extremist and terrorism-related content.