naivepy 1.1
Naive Algorithm Module Implemented in Python
Keywords: naive,naive bayes,algorithm,naive algorithm,classification,module

# NaivePy

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# This Module Is No Longer Maintained
v1.1 is the last release.

# Naive Bayes :
## About Naive Bayes :
<p align="Justify">
Naïve Bayes algorithm is a supervised learning algorithm, which is based on Bayes theorem and used for solving classification problems.</br>
It is mainly used in text classification that includes a high-dimensional training dataset.</br>
Naïve Bayes Classifier is one of the simple and most effective Classification algorithms which helps in building the fast machine learning models that can make quick predictions.</br>
It is a probabilistic classifier, which means it predicts on the basis of the probability of an object.</br>
Some popular examples of Naïve Bayes Algorithm are spam filtration, Sentimental analysis, and classifying articles.
</p>

## Formula Of Naive Bayes :
<p align="justify">
Bayes' theorem is also known as Bayes' Rule or Bayes' law, which is used to determine the probability of a hypothesis with prior knowledge. It depends on the conditional probability.
The formula for Bayes' theorem is given as:
Naïve Bayes Classifier Algorithm
Where,

**$P(A|B)$ = ${P(B|A)P(A)} \over P(B)$**

P(A|B) is Posterior probability: Probability of hypothesis A on the observed event B.

P(B|A) is Likelihood probability: Probability of the evidence given that the probability of a hypothesis is true.

P(A) is Prior Probability: Probability of hypothesis before observing the evidence.

P(B) is Marginal Probability: Probability of Evidence.
</p>

# Documentation:
Read the [Docs Here](https://naivepy.readthedocs.io/en/latest/#)

# Installation :
To Install the module
```
pip install naivepy
```

# About Module:
<p align="justify">
Naivepy module is built using python and pandas. It is and machine learning algorithm. This Module can take the target column and classifies it.

**Note** : The Target Column must have 2 Types of values other wise MaxTargetColumnException will be occured.

# Examples :

**Code** :
```
from naivepy import Naive

n=Naive(filename="data.csv",sample_list=["red","suv","domestic"],target_column="stolen")
print(n.getans)
print(n.getdata)
print(n.getlabel)
```

**Output** :
```
        Color    Type    Origin Stolen
   0     Red  Sports  Domestic    Yes
   1     Red  Sports  Domestic     No
   2     Red  Sports  Domestic    Yes
   3  Yellow  Sports  Domestic     No
   4  Yellow  Sports  Imported    Yes
   5  Yellow     SUV  Imported     No
   6  Yellow     SUV  Imported    Yes
   7  Yellow     SUV  Domestic     No
   8     Red     SUV  Imported     No
   9     Red  Sports  Imported    Yes
   No
   0.072
```

# Author : Prathamesh Dhande