**代碼使用多項式回歸模型和fastapi預測房價**`
使類有一個引數并有一個 4 值
class features(BaseModel):
X2_house_age: float
X3_distance_to_the_nearest_MRT_station: float
X4_number_of_convenience_stores: float
year: int
#train_plynomial_model 是一個接受特征并回傳多項式模型的函式
@app.post("/predict")
def train_plynomial_model(req : features):
X2_house_age=req.X2_house_age
X3_distance_to_the_nearest_MRT_station=req.X3_distance_to_the_nearest_MRT_station
X4_number_of_convenience_stores=req.X4_number_of_convenience_stores
year=req.year
features = list([X2_house_age,
X3_distance_to_the_nearest_MRT_station,
X4_number_of_convenience_stores,
year
])
poly = PolynomialFeatures(2)
poly_x_train = poly.fit_transform(features)
newfeatures= model.fit(poly_x_train, model.y_train)
newfeature=newfeatures.reshape(-1, 1)
return(newfeature)
predict 是一個預測房價的函式
async def predict(train_plynomial_model):
newfeature=train_plynomial_model.newfeatures
prediction = model.predict([ [ newfeature] ])
return {'you can sell your house for {} '.format(prediction)}
``
我試著把這句話newfeature=newfeature.reshape(-1, 1)
uj5u.com熱心網友回復：
您應該更改features陣列而不是newfeatures。
嘗試像這樣重塑并使用 numpy 陣列：
features = np.array(features).reshape((len(features), 1))
轉載請註明出處，本文鏈接：https://www.uj5u.com/houduan/531547.html
標籤：Pythonpython-3.x机器学习线性回归快速API
上一篇：OpenGL ES EGL eglDestroySurface
下一篇：Java組合異步編程（2）