Fragnance Price Prediction

[aryantiwari10]

Define You:

• [x] LGM-SOC'21 Participant
• [ ] DevIncept Participant
• [x] Contributor

PROJECT TITLE : Fragnance Price Prediction

GOAL : To predict the price of the fragnances .

DATASET : https://www.kaggle.com/aryantiwari123/pricelistcsv

WHAT I HAD DONE : In this project first I performed a exploratory data analysis on the Pricelist dataset which includes of data cleaning , data manipulation, data preprocessing , data visualization and after that I did the model building using different machine learning classification and regression algorithms and then predicted the accuracy of every model . In the model prediction part I used total 10 machine learning algos . In each algo I had included the accuracy score , training score , classification report , confusion matrix . While in the EDA part I have included different plots for the different visualizations of our dataset .

MODELS USED : I used total 10 machine leaning algos in the dataset

Logistic Regression : 62.40 %

KNeighborsClassifier : 60.46%

SVC : 62.45 %

Naive Bayes : 60.26%

DECISION TREE CLASSIFIER : 70.07%

RandomForestClassifier : 74.77%

AdaBoostClassifier : 34.29%

Gradient Boosting Classifier : 73.90%

ExtraTreesClassifier : 78.7%%

Bagging Classifier : 98.47%

LIBRARIES:

PANDAS

NUMPY

MATPLOTLIB

SEABORN

SCIPY

SKLEARN

CONCLUSION :

So we get a good accuracy score of 98.47 % using the Bagging Classifier.

[prathimacode-hub]

Amazing, issue assigned. Follow the project structure and complete the PR. @aryantiwari10