# Creating a simple machine learning model

Create a Linear Regression Model in Python using a randomly created data set.

Linear Regression Model
Linear regression geeks for geeks

Generating the Training Set

 `# python library to generate random numbers ` `from` `random ``import` `randint ` ` `  `# the limit within which random numbers are generated ` `TRAIN_SET_LIMIT ``=` `1000` ` `  `# to create exactly 100 data items ` `TRAIN_SET_COUNT ``=` `100` ` `  `# list that contains input and corresponding output ` `TRAIN_INPUT ``=` `list``() ` `TRAIN_OUTPUT ``=` `list``() ` ` `  `# loop to create 100 data  items with three columns each ` `for` `i ``in` `range``(TRAIN_SET_COUNT): ` `    ``a ``=` `randint(``0``, TRAIN_SET_LIMIT) ` `    ``b ``=` `randint(``0``, TRAIN_SET_LIMIT) ` `    ``c ``=` `randint(``0``, TRAIN_SET_LIMIT) ` ` `  `# creating the output for each data item ` `    ``op ``=` `a ``+` `(``2` `*` `b) ``+` `(``3` `*` `c) ` `    ``TRAIN_INPUT.append([a, b, c]) ` ` `  `# adding each output to output list ` `    ``TRAIN_OUTPUT.append(op) `

Machine Learning Model – Linear Regression

The Model can be created in two steps:-
1. Training the model with Training Data
2. Testing the model with Test Data

Training the Model
The data that was created using the above code is used to train the model

 `# Sk-Learn contains the linear regression model ` `from` `sklearn.linear_model ``import` `LinearRegression ` ` `  `# Initialize the linear regression model ` `predictor ``=` `LinearRegression(n_jobs ``=``-``1``) ` ` `  `# Fill the Model with the Data ` `predictor.fit(X ``=` `TRAIN_INPUT, y ``=` `TRAIN_OUTPUT) `

Testing the Data
The testing is done Manually. Testing can be done using some random data and testing if the model gives the correct result for the input data.

 `# Random Test data ` `X_TEST = [[ 10, 20, 30 ]] ` ` `  `# Predict the result of X_TEST which holds testing data ` `outcome = predictor.predict(X = X_TEST) ` ` `  `# Predict the coefficients ` `coefficients = predictor.coef_ ` ` `  `# Print the result obtained for the test data ` `print(``'Outcome : {}\nCoefficients : {}'``.format(outcome, coefficients)) `

The Outcome of the above provided test-data should be, 10 + 20*2 + 30*3 = 140.
Output

```Outcome : [ 140.]
Coefficients : [ 1. 2. 3.]
```

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