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author | Indrajith K L | 2022-12-03 17:00:20 +0530 |
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committer | Indrajith K L | 2022-12-03 17:00:20 +0530 |
commit | f5c4671bfbad96bf346bd7e9a21fc4317b4959df (patch) | |
tree | 2764fc62da58f2ba8da7ed341643fc359873142f /v_windows/v/old/examples/linear_regression | |
download | cli-tools-windows-master.tar.gz cli-tools-windows-master.tar.bz2 cli-tools-windows-master.zip |
Diffstat (limited to 'v_windows/v/old/examples/linear_regression')
-rw-r--r-- | v_windows/v/old/examples/linear_regression/simple_linear_regression.v | 55 |
1 files changed, 55 insertions, 0 deletions
diff --git a/v_windows/v/old/examples/linear_regression/simple_linear_regression.v b/v_windows/v/old/examples/linear_regression/simple_linear_regression.v new file mode 100644 index 0000000..5bce1dc --- /dev/null +++ b/v_windows/v/old/examples/linear_regression/simple_linear_regression.v @@ -0,0 +1,55 @@ +import math + +struct LinearResult { + r2 f64 + intercept f64 + slope f64 + dependent_variable_means f64 + independent_variable_means f64 +} + +fn linearrelationship(independent_variable []int, dependent_variable []int) LinearResult { + // Objective : + // Find what is the linear relationship between two dataset X and Y? + // x := independent variable + // y := dependent variable + mut sum_r2_x := 0 + mut sum_r2_y := 0 + mut sum_xy := 0 + mut sum_x := 0 + mut sum_y := 0 + for i in independent_variable { + sum_x += i + sum_r2_x += i * i + } + for yi in dependent_variable { + sum_y += yi + sum_r2_y += yi * yi + } + x_means := sum_x / independent_variable.len + y_means := sum_y / dependent_variable.len + for index, x_value in independent_variable { + sum_xy += x_value * dependent_variable[index] + } + // /Slope = (∑y)(∑x²) - (∑x)(∑xy) / n(∑x²) - (∑x)² + slope_value := f64((sum_y * sum_r2_x) - (sum_x * sum_xy)) / f64((sum_r2_x * independent_variable.len) - (sum_x * sum_x)) + // /Intercept = n(∑xy) - (∑x)(∑y) / n(∑x²) - (∑x)² + intercept_value := f64((independent_variable.len * sum_xy) - (sum_x * sum_y)) / f64((independent_variable.len * sum_r2_x) - (sum_x * sum_x)) + // Regression equation = Intercept + Slope x + // R2 = n(∑xy) - (∑x)(∑y) / sqrt([n(∑x²)-(∑x)²][n(∑y²)-(∑y)²] + r2_value := f64((independent_variable.len * sum_xy) - (sum_x * sum_y)) / math.sqrt(f64((sum_r2_x * independent_variable.len) - (sum_x * sum_x)) * f64((sum_r2_y * dependent_variable.len) - (sum_y * sum_y))) + return LinearResult{ + r2: r2_value + intercept: intercept_value + slope: slope_value + independent_variable_means: x_means + dependent_variable_means: y_means + } +} + +fn main() { + independent_variable := [4, 5, 6, 7, 10] + dependent_variable := [3, 8, 20, 30, 12] + result := linearrelationship(independent_variable, dependent_variable) + println(result) +} |