feat(knowing app): stm32f4 logistic regression iris demo

APP_Framework/Applications/knowing_app/iris_ml_demo/LogisticRegressionModel.h

@@ -0,0 +1,41 @@
+#include <stdarg.h>
+
+/**
+ * Compute dot product
+ */
+float dot(float *x, ...)
+{
+    va_list w;
+    va_start(w, 4);
+    float dot = 0.0;
+
+    for (int i = 0; i < 4; i++) {
+        const float wi = va_arg(w, double);
+        dot += x[i] * wi;
+    }
+
+    return dot;
+}
+
+/**
+ * Predict class for features vector
+ */
+int predict(float *x)
+{
+    float votes[3] = {0.0f};
+    votes[0] = dot(x, -0.423405592418, 0.967388282125, -2.517050233286, -1.079182996654) + 9.84868307535428;
+    votes[1] = dot(x, 0.534517184386, -0.321908835083, -0.206465997471, -0.944448257908) + 2.238120068472271;
+    votes[2] = dot(x, -0.111111591968, -0.645479447042, 2.723516230758, 2.023631254562) + -12.086803143826813;
+    // return argmax of votes
+    int classIdx = 0;
+    float maxVotes = votes[0];
+
+    for (int i = 1; i < 3; i++) {
+        if (votes[i] > maxVotes) {
+            classIdx = i;
+            maxVotes = votes[i];
+        }
+    }
+
+    return classIdx;
+}

APP_Framework/Applications/knowing_app/iris_ml_demo/iris_ml_demo.c

@@ -76,3 +76,23 @@ void iris_DecisonTree_predict()
 #ifdef __RT_THREAD_H__
 MSH_CMD_EXPORT(iris_DecisonTree_predict, iris predict by decison tree classifier);
 #endif
+
+void iris_LogisticRegression_predict()
+{
+#include "LogisticRegressionModel.h"
+    int result;
+
+    simple_CSV_read();
+
+    for (int i = 0; i < data_len; i++) {
+        result = predict(data[i]);
+        printf("data %d: ", i + 1);
+        for (int j = 0; j < FEATURE_NUM; j++) {
+            printf("%.4f ", data[i][j]);
+        }
+        printf("result: %d\n", result);
+    }
+}
+#ifdef __RT_THREAD_H__
+MSH_CMD_EXPORT(iris_LogisticRegression_predict, iris predict by logistic regression);
+#endif