# Naive bayes model excel jobs

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

...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

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.

...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

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

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:

...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

Implementation of **Naive** **Bayes** and Random Forest classifiers.

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

...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

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**.

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.

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

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.

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

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

...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

technical writing for **naive** **Bayes** classification in R

...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