Topic: abalone Goto Github
Some thing interesting about abalone
Some thing interesting about abalone
abalone,ABALONE_DECISIONTREE_C4-5: A procedure is attached that uses the Abalone file (https://archive.ics.uci.edu/ml/datasets/abalone) as test and training . After evaluating the entropy of each field, a tree has been built with the nodes corresponding to fields 0, 7 and 4 and branch values ??in each node: 1 for the root node corresponding to field 0, 29 for the next node in the hierarchy corresponding to field 7, and 33 in the last node corresponding to field 4. The values ??of each field have been associated with indices, which can encompass several real values. the values ??of these indices are those that have been considered for the calculation of entropies and for making a branching of values ??at each node. A hit rate of around 58% is obtained, that is, in the low range of the existing procedures to treat this multiclass file, which are detailed in the documentation to download from https://archive.ics.uci.edu/ml/ datasets / abalone The depth of the tree has been increased without obtaining significant improvements. Nor has it been significantly improved by applying adaboost. Resources: Spyder 4 On the c: drive there should be the abalone-1.data file downloaded from https://archive.ics.uci.edu/ml/datasets/abalone Functioning: From Spyder run: AbaloneDecisionTree_C4-5-ThreeLevels.py The screen indicates the number of hits and failures and in the file C:\AbaloneCorrected.txt the records of the test file (records 3133 to 4177 of abalone-1.data) with an indication of whether their predicted class values ??coincide with the reals, the predicted class value and the order number of the record in abalone-1.data The following programs are also attached: AbaloneDecisionTree_ID3.py and AbaloneDecisionTree_C4-5_parameters.py that have served to calculate the necessary parameters to build the tree. Cite this software as: ** Alfonso Blanco GarcΓa ** ABALONE_DECISIONTREE_C4-5 References: https://archive.ics.uci.edu/ml/datasets/abalone
User: ablanco1950
abalone,ABALONE_NAIVEBAYES_WEIGHTED_ADABOOST: Two procedures are attached that use the Abalone file as test and training (https://archive.ics.uci.edu/ml/datasets/abalone). Both start from a treatment of the training part calculating the frequencies corresponding to each value of each field and applying a Naive Bayes probability calculation. In a second step, one of the procedures takes advantage of the previous result to apply weights based on each field to the wrong or true records. The other procedure uses Adaboost, using the adaboost routine published at https://github.com/jaimeps/adaboost-implementation (Jaime Pastor). A hit rate of around 58% is obtained, that is, in the low range of the existing procedures to treat this multiclass file, which are detailed in the documentation to download from https://archive.ics.uci.edu/ml/ datasets / abalone
User: ablanco1950
abalone,Using the Sklearn classifiers: Naive Bayes, Random Forest, Adaboost, Gradient Boost, Logistic Regression and Decision Tree good success rates are observed in a very simple manner. In this work sensitivity is also considered. Treating each record individually, differences are found in the results for each record depending on the model used, which is hidden in treatments that compute a total volume of data
User: ablanco1950
abalone,Abalone game in wpf/c#. With the possibility to play against human or computer agent
User: amitstreit
abalone,Performing classification tasks with the LibSVM toolkit on four different datasets: Iris, News, Abalone, and Income.
User: andi611
abalone,Environmental DNA reflects common mitochondrial haplotypic variation
User: clare-edna
abalone,Machine Learning Classification on Abalone Dataset
User: darshilmaru01
abalone,This Repository contains machine learning classification projects
User: dinabandhu50
abalone,Simple ML project using UCI dataset
User: dtroupe18
abalone,A study about the UCI's abalone dataset
User: fnbalves
abalone,GPoFM: Gaussian Process Training with Optimized Feature Maps for Shift-Invariant Kernels
User: maxingaussian
abalone,Blacklip Abalone (Haliotis rubra) PCA Analysis
User: melissalaurino
abalone,Predicting the age of abalone from physical measurements.
User: mukundkal
abalone,Simplified Abalone game for school
User: nathanfallet
abalone,Predicting the age of abalone using multiple regression in R
User: nishitpatel01
abalone,Abalone Gender Classification
User: noahgift
abalone,The Abalone project is a Java-based implementation of the classic multiplayer board game. The game is designed to be played by 2 to 4 players and challenges players to use strategy and skill to maneuver their marbles on the game board with the goal of pushing their opponent's marbles off the edge.
User: pranav2106
abalone,implementation of kNN, Decision Tree, Random Forest, and SVM algorithms for classification and regression applied to the abalone dataset.
User: renanleonel
abalone,Study on impact of different algorithms on regression models for abalone dataset.
User: rpatelpj
abalone,A Python implementation of the board game Abalone intended to be played by artificial intelligence
User: scriptim
abalone,Abalone Data Set
Organization: semnan-university-ai
Home Page: http://archive.ics.uci.edu/ml/datasets/Abalone
abalone,A third year group project.
User: simi27
Home Page: https://github.com/simi27/Abalone-3rdYearProject
abalone,An environment of the board game Abalone using OpenAI's Gym API
User: towzeur
abalone,Website to play Abalone game online.
User: vincentfrochot
Home Page: http://www.abal.online
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