Updates README

Author: Adwaith-Rajesh

README.md

@@ -25,42 +25,89 @@ to grow with me as I learn new Machine Learning Algo or anything similar
 ### Example
 
 ```c
+#define INCLUDE_MAT_CONVERSIONS
 #include "ds/mat.h"
-#include "ml/linregress.h"
-#include "model/serializer.h"
+#include "ml/logisticregress.h"
+#include "model/metrics.h"
 #include "model/train_test_split.h"
 #include "parsers/csv.h"
 
 int main(void) {
-    CSV *csv_reader = csv_init(1000, 3, ',');
-    csv_parse(csv_reader, "data/placement.csv");
-
-    Mat *X = csv_get_mat(csv_reader, (int[]){0}, 1);
-    Mat *Y = csv_get_mat(csv_reader, (int[]){2}, 1);
+    CSV *csv_reader = csv_init(569, 31, ',');
+    csv_parse(csv_reader, "data/bcancer.csv");
 
+    Mat *X = csv_get_mat_slice(csv_reader, (Slice){1, 31});
+    Mat *Y = csv_get_mat_slice(csv_reader, (Slice){0, 1});
     Mat *X_train, *X_test, *Y_train, *Y_test;
-    train_test_split(X, Y, &X_train, &X_test, &Y_train, &Y_test, 0.3, 100);
 
-    LinearRegressionModel *model = linregress_init();
-    linregress_fit_mat(model, X_train, Y_train);
-    // model_deserialize(model, LinearRegression, "placement.model");
+    train_test_split(X, Y, &X_train, &X_test, &Y_train, &Y_test, 0.3, 101);
+
+    logregress_set_max_iter(2000);
+    LogisticRegressionModel *model = logregress_init();
+    logregress_fit(model, X_train, Y_train);
 
-    printf("score: %lf\n", linregress_score_mat(model, X_test, Y_test));
-    printf("slope: %lf\n", model->slope);
-    printf("intercept: %lf\n", model->intercept);
-    printf("rvalue: %lf\n", model->rvalue);
+    Array *preds = logregress_predict_many(model, X_test);
+    Array *true = mat_get_col_arr(Y_test, 0);
 
-    model_serialize(model, LinearRegression, "placement.model");
+    logregress_print(model);
 
-    linregress_free(model);
-    mat_free_many(6, X, Y, X_train, X_test, Y_train, Y_test);
+    printf("confusion matrix: \n");
+    Mat *conf_mat = model_confusion_matrix(true, preds);
+    mat_print(conf_mat);
+
+    arr_free(true);
+    arr_free(preds);
+    logregress_free(model);
+    mat_free_many(7, X, Y, X_test, X_train, Y_test, Y_train, conf_mat);
     csv_free(csv_reader);
 }
 ```
 
-The dataset used can be found [here](https://www.kaggle.com/datasets/mayurdalvi/simple-linear-regression-placement-data)
-This dataset should no be trained on a Linear Regression Model. As of writing this README,
-Logistic Regression is not yet implemented so we are stuck with this.
+<details>
+  <summary>Output</summary>
+
+```console
+LogisticRegressionModel(bias: 0.5159147, loss: -12.4263621, weights: 0x5556e8a732c0)
+weights:
+1546.6922009
+1139.6829595
+8552.1648900
+2522.0044946
+11.8724211
+-19.3345598
+-44.9646156
+-18.4984994
+23.8378678
+10.1676564
+0.2338315
+103.3839701
+-139.7864354
+-4498.8563443
+0.2662770
+-6.5798244
+-8.6158697
+-1.6938180
+1.6508702
+-0.3857419
+1650.7843571
+1445.0283208
+8312.7672485
+-4024.9280673
+13.2972726
+-72.4527931
+-111.8298475
+-26.6204266
+28.0612275
+5.4099162
+confusion matrix:
+  57.00   10.00
+  2.00   101.00
+
+```
+
+</details>
+
+The dataset used can be found [here](https://gitlab.com/adwaithrajesh/linear-ml-test/-/blob/main/data/bcancer.csv?ref_type=heads). which is a modified version of [this](https://www.kaggle.com/datasets/uciml/breast-cancer-wisconsin-data) dataset
 
 ### Docs