Stock-closing-rate-predictor

Predict the closing rate of stock using stock market dataset features by Yahoo Finance.

Dataset - Time Series data

Name- Yahoo Finance Nifty dataset Source- Yahoo Finance (https://in.finance.yahoo.com/quote/%5ENSEI/history/)

Dataset Description

● 7 Attributes with 250 Rows. ● Attributes are as ‘Date’, ‘Open’, ‘Close’, ‘High’, ‘Low’, ‘Adj Close’, ‘Volume’. ● Attributes ‘Close’ act as label here i.e, Dependent variable. ● Remaining attributes are defined as features i.e, Independent variables. ● Time period : 22-Nov-2019 - 22-Nov-2020 ● Frequency : Daily

Data Preprocessing

● Importing the dataset into Pandas DataFrame format from .csv file. ● Splitting the dataset into the Training set and Test set using train_test_split. ● Taking care of missing data using SimpleImputer to fill ‘mean’ value to Null values. ● Feature Scaling the dataset values using StandardScaler to bring all into same scale

Supervised learning

Linear Regression is used as Supervised learning method to predict the label i.e, ‘Close’ value of a stock using various attributes like ‘Date’, ‘Open’, ‘High’, ‘Low’, ‘Adj Close’, ‘Volume’ as features to the Regression model.