Exemplos de uso de Classification algorithms em Inglês e suas traduções para o Português
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The group of classification algorithms has two possible setups.
Consolidated output of six precisely chosen classification algorithms.
In particular, in neuroscience, classification algorithms were used to test hypotheses about the functioning of the central nervous system.
There are a growing number of technologies that make use of classification algorithms for automating tasks.
Six classification algorithms have been tested as to its ability to sort the permeability of rock in four distinct classes low:< 1md, intermediate: 1-10md, high: 10-100md, excellent:>100md.
The selection of the most relevant features from a dataset usually benefits the performance obtained by classification algorithms.
Classification algorithms, based on morphological criteria and establishing five main groups of patterns nuclear, nucleolar, cytoplasmic, mitotic apparatus and mixed were prepared.
The use of differential reflectivity(formula_1),in combination with horizontal reflectivity(formula_2) has led to a variety of hail classification algorithms.
The experiments here described use automatic learning,with three of the best known classification algorithms, naïve bayes, nearest neighbor(1bk) and j48(weka version of c4.5) with a 4- fold cross validation.
This work approaches the automatic identification of cattle behavior, using animals¿movement andpositioning data and supervised classification algorithms.
One of the most widely used data classification algorithms in the literature is the support vector machine which, despite possessing positive features in its application, is sensitive to control parameters.
It uses the combined power of neural networks(such as deep learning and long short-term memory) anda handpicked group of six classification algorithms.
These pattern classification algorithms are able to incorporate previous knowledge in the form of similarity functions, i.e., a kernel, and it has been successful in a wide range of supervised learning problems.
It uses the combined power of neural networks(such as deep learning and long short-term memory) anda handpicked group of six classification algorithms.
Predict for prediction configuration and serving, Regress for regression modeling,Classify for classification algorithms, and Multi-inference for combining Regress and Classify api usage together.
Moreover, not all plaque components are identified by the method: intraluminal thrombus, for example,is not included in contemporary classification algorithms.
This work proposes an exploratory study on the use of different classification algorithms, of selection metrics, and grouping to build crossproject defect predictions models.
The use of differential reflectivity(Z d r{\displaystyle Z_{dr}}), in combination with horizontal reflectivity( Z h{\displaystyle Z_{h}}) has led to a variety of hail classification algorithms.
They end up doing a manual search tools like weka, rapidminer, torch or pybrain,which allow the selection of classification algorithms and their parameters to induce a classifier given a database.
Classification algorithms covered in this course include nearest neighbor algorithm, support vector machine(SVM)algorithm, Bayesian methods, decision trees, lists of rules.
Through the use of data mining techniques,more usually the classification algorithms, it is possible to implement predictive models that are able to early identify a student in risk of dropout.
Therefore, it was studied the application of 8 classification algorithms, 6 feature selection, and a cluster in a data set with 1283 projects, resulting in the construction of 61584 different prediction models.
Deep-learning-based target classification algorithm for auto-tracking 2.0 and perimeter protectio.
The proposed method used random forest as classification algorithm and relieff for feature selection.
In addition to important discussions regarding critical aspects in the methodology for determination of autoantibodies,novel HEp-2 ANA patterns were characterized and incorporated into the classification algorithm.
However, there isn't a lack of tools orguidelines to aid developers in the selection of classification algorithm to be used by classifier.
In order to assign a causal relation between HIV infection and pregnant and/or postpartum conditions,it was necessary to use information contained in the classification algorithm.
A high spatial resolution image of a densely built-up area/ A grayscale image of buildings detected by the neural network classification algorithm.
The data extracted from the model was used to train a svm(support vector machine) classification algorithm.
Analysis with a large number of variables generally requires a large amount of memory and computation power,also it may cause a classification algorithm to overfit to training samples and generalize poorly to new samples.