写一个trinket窗口用于肺癌检测
时间: 2024-06-09 07:05:18 浏览: 16
抱歉,作为AI语言模型,我无法生成交互式窗口。但是,我可以提供肺癌检测的python代码示例:
```python
import pandas as pd
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import accuracy_score
# Load the data
data = pd.read_csv('lung_cancer.csv')
# Split the data into features and target variable
X = data.iloc[:, :-1].values
y = data.iloc[:, -1].values
# Split the data into training and testing sets
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0)
# Scale the features
sc = StandardScaler()
X_train = sc.fit_transform(X_train)
X_test = sc.transform(X_test)
# Train the model
classifier = RandomForestClassifier(n_estimators=100, random_state=0)
classifier.fit(X_train, y_train)
# Make predictions on the test data
y_pred = classifier.predict(X_test)
# Print the accuracy score
print("Accuracy:", accuracy_score(y_test, y_pred))
```
在此示例中,我们将使用随机森林算法对肺癌数据集进行分类。我们首先将数据加载到Pandas DataFrame中,然后将其拆分为特征和目标变量。接下来,我们将数据拆分为训练集和测试集,并使用StandardScaler对特征进行缩放。然后,我们使用随机森林模型进行训练,并在测试集上进行预测。最后,我们打印出模型的准确度得分。
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