Naive bayes model excel jobs


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    analysis data 6 days left

    Use the attached train and test data set, build the classification models based...on the training set, and evaluate the models based on the test set. Compare the accuracies to tell which model is the best one. In terms of the classification techniques, you should utilize logistical regression, KNN classifier, and Naïve Bayes classifications. Use R

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    ...analysis and principle components analysis on the predictors 4. Run cluster analysis on the predictors 5. Run various machine learning algorithms (such as regression, SVM, Naive Bayesian) on the data either as a regression problem (assume the outcome value is continuous) or classification problem (assume the outcome value is 1/0) I do not care the

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    I built a Naive Bayes model and I need someone just to make the Roc Curve. The code is available in github and I have 3 hours to complete.

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    ...algorithm works best in classifying new movie in terms of accuracy. The three algorithms are J48 Decision Tree, Naive Bayes and Neural Networks. 2. From number 1, select the best performing algorithm and build the model. 3. The model built will be ingested in a web application or desktop application or mobile application that will classify new

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    we need freelancer who can grasp and handle arabic content, and have ability to do reprocessing and applying multiple classification on this (SVM , navies bayes and decision tree) time duration is limited in 4-5 days only programming language not specified in one language

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    For example, you can include k-Nearest Neighbor (KNN), Decision Trees, Artificial Neural Networks (ANN), Support Vector Machines (SVM), Random Forest, Naïve Bayes and/or Logistic Regression type models in your comparative analysis. Here are some of the specifics for this assignment:

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    ...classification algorithms on this data to finally measure the accuracy and performance of each classifier: Artificial Neural Network SVM Random Forest Decision Tree Naive Bayes Logistic regression KNN I need the following criteria to be measured in the form of graphs and tables: sensitivity = true positive rate specificity = true negative

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    Implementation of Naive Bayes and Random Forest classifiers.

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    Implementing the naive bayes and random forest on mushroom dataset. Generating roc curves for poisonous and edible attributes generated.

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    ...application is located, and it will create a package for MacOS from it, if such thing is possible, or some other sort of single-file distributable container/installer. Maybe I am naive, maybe there are more things required, like some signing keys, registration at apple, etc ... I don't know. (I do not need to publish in apple store, by the way, only run it

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    Implement a Naïve Bayes Classifier

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    Analysis analysts' comment and stock predic...word, stemming, filter tokens, bag-of-words model, TF-IDF model, TF-IDF Weighted Averaged Word Vectors, Naive Bayes algorithm & KNN algorithm. [Removed for encouraging offsite communication which is against our Terms and Conditions -Section 13:Communication With Other Users] *Dataset is provided by excel.

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    Expert writers are needed to write research work of 5000 word on the topic : "Optimum portfolio vs naive portfolio selection". Only the writers who have the knowledge of Harvard style writing and finance need to apply.

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    Research writing of 5000 words is needed. The topic of the research project is "Optimum portfolio vs naive portfolio selection".

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    Expert writers are needed to write research work of 5000 word on the topic : "Optimum portfolio vs naive portfolio selection". Only the writers who have the knowledge of Harvard style writing and finance need to apply.

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    train a data set consisting of weather data and when some new set is sent by the user then the probability should be sent for the event to occur or not

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    I need a logo designed. Maroon or Royal Naive background. ( RS ) in Gold with a plain crown above it. Text beneath " Revolution Soldiers "

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    ...sampled independently from an identical distribution. A popular machine learning approach to text classification is Naive Bayes model which tries to predict the probability of text (x) belonging to a class (y), p(y|x), using the Bayes theorem. It assumes the class conditional distribution p(x|y) to be independently and identically distributed across

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    ...exercise with three simple tasks: In the exercise, we will analyze experimental data using mixed-model methodology. The exercise has three main parts: 1. Analyze the data according to the mixed models methodology. 2. Re-analyze the data using naive linear regression and comparing the results. 3. Use parametric bootstrap to approximate the bias

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