Movie Reviews
Determine whether a given movie review is a positive review or negative review.

Language: Python.
Software Summary: I created a classifier that receives a directory with negative and positive movie reviews. My algorithm then goes through each review and determines whether they are a positive or negative review based from a positive and negative word list. Based from this information, it will produce the percentage of correctly classified instances.

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Decision Tree
Analyzes data to determine what the best method of achieving an outcome is.

Language: Python.
Software Summary: Using gain and entropy, this algorithm will look at a set of data to predict the best possible and shortest way to create a decision tree from it. This algorithm will display the best tree as output. I was given the dtree.py file and was required to code the following methods: entroy, gain, getBestAttribute, id3.

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Naive Bayes
Analyzes, learns and tests a dataset for classification.

Language: Python.
Software Summary: This algorithm is used to classify data accurately using probabilities with Naive Bayes algorithm. For testing purposes, I used a large chess dataset, but any dataset can be used using this algorithm assuming there are no missing values. Within the dataset, there are several attributes along with an outcome. This algorithm will train based off the given dataset and will be able to predict the outcome of new data given the knowledge of the training dataset. For instance, if the outlook is sunny, the wind is weak and the temperature is hot, the outcome is that you will play tennis. This algorithm can be used to predict whether you will play tennis given the values of the attributes of outlook, wind and temperature.

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