使用用户输入测试预测模型
Testing Prediction Model with User Input
我是 ML 的初学者,但是我正在做一个大学项目,我能够成功地训练模型,但我不确定如何测试用户输入。我的项目是检查一个人输入的数据是否是糖尿病。
CSV 数据:
Pregnancies Glucose BloodPressure SkinThickness Insulin BMI DiabetesPedigreeFunction Age Outcome
6 148 72 35 0 33.6 0.627 50 1
1 85 66 29 0 26.6 0.351 31 0
8 183 64 0 0 23.3 0.672 32 1
1 89 66 23 94 28.1 0.167 21 0
0 137 40 35 168 43.1 2.288 33 1
5 116 74 0 0 25.6 0.201 30 0
3 78 50 32 88 31 0.248 26 1
10 115 0 0 0 35.3 0.134 29 0
2 197 70 45 543 30.5 0.158 53 1
代码:
from sklearn.ensemble import RandomForestClassifier
random_forest_model = RandomForestClassifier(random_state=10)
random_forest_model.fit(X_train, y_train.ravel())
predict_train_data = random_forest_model.predict(X_test)
from sklearn import metrics
print("Accuracy = {0:.3f}".format(metrics.accuracy_score(y_test, predict_train_data)))
用户输入代码:
print("Enter your own data to test the model:")
pregnancy = int(input("Enter Pregnancy:"))
glucose = int(input("Enter Glucose:"))
bloodpressure = int(input("Enter Blood Pressue:"))
skinthickness = int(input("Enter Skin Thickness:"))
insulin = int(input("Enter Insulin:"))
bmi = float(input("Enter BMI:"))
DiabetesPedigreeFunction = float(input("Enter DiabetesPedigreeFunction:"))
age = int(input("Enter Age:"))
userInput = [pregnancy, glucose, bloodpressure, skinthickness, insulin, bmi,
DiabetesPedigreeFunction, age]
我想要 return 1 - 如果是糖尿病或 0 - 如果不是糖尿病
编辑 - 添加了 x_train 和 y_train:
from sklearn.model_selection import train_test_split
feature_columns = ['Pregnancies', 'Glucose', 'BloodPressure', 'SkinThickness', 'Insulin', 'BMI', 'DiabetesPedigreeFunction', 'Age']
predicted_class = ['Outcome']
X = data[feature_columns].values
y = data[predicted_class].values
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.30, random_state=10)
from sklearn.ensemble import RandomForestClassifier
random_forest_model = RandomForestClassifier(random_state=10)
random_forest_model.fit(X_train, y_train.ravel())
尝试
result = random_forest_model.predict([user_input])[0]
因为模型需要多个输入(二维数组)和 returns 每个元素的预测(观察列表)。
我是 ML 的初学者,但是我正在做一个大学项目,我能够成功地训练模型,但我不确定如何测试用户输入。我的项目是检查一个人输入的数据是否是糖尿病。
CSV 数据:
Pregnancies Glucose BloodPressure SkinThickness Insulin BMI DiabetesPedigreeFunction Age Outcome
6 148 72 35 0 33.6 0.627 50 1
1 85 66 29 0 26.6 0.351 31 0
8 183 64 0 0 23.3 0.672 32 1
1 89 66 23 94 28.1 0.167 21 0
0 137 40 35 168 43.1 2.288 33 1
5 116 74 0 0 25.6 0.201 30 0
3 78 50 32 88 31 0.248 26 1
10 115 0 0 0 35.3 0.134 29 0
2 197 70 45 543 30.5 0.158 53 1
代码:
from sklearn.ensemble import RandomForestClassifier
random_forest_model = RandomForestClassifier(random_state=10)
random_forest_model.fit(X_train, y_train.ravel())
predict_train_data = random_forest_model.predict(X_test)
from sklearn import metrics
print("Accuracy = {0:.3f}".format(metrics.accuracy_score(y_test, predict_train_data)))
用户输入代码:
print("Enter your own data to test the model:")
pregnancy = int(input("Enter Pregnancy:"))
glucose = int(input("Enter Glucose:"))
bloodpressure = int(input("Enter Blood Pressue:"))
skinthickness = int(input("Enter Skin Thickness:"))
insulin = int(input("Enter Insulin:"))
bmi = float(input("Enter BMI:"))
DiabetesPedigreeFunction = float(input("Enter DiabetesPedigreeFunction:"))
age = int(input("Enter Age:"))
userInput = [pregnancy, glucose, bloodpressure, skinthickness, insulin, bmi,
DiabetesPedigreeFunction, age]
我想要 return 1 - 如果是糖尿病或 0 - 如果不是糖尿病
编辑 - 添加了 x_train 和 y_train:
from sklearn.model_selection import train_test_split
feature_columns = ['Pregnancies', 'Glucose', 'BloodPressure', 'SkinThickness', 'Insulin', 'BMI', 'DiabetesPedigreeFunction', 'Age']
predicted_class = ['Outcome']
X = data[feature_columns].values
y = data[predicted_class].values
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.30, random_state=10)
from sklearn.ensemble import RandomForestClassifier
random_forest_model = RandomForestClassifier(random_state=10)
random_forest_model.fit(X_train, y_train.ravel())
尝试
result = random_forest_model.predict([user_input])[0]
因为模型需要多个输入(二维数组)和 returns 每个元素的预测(观察列表)。