我从Azure机器学习下载了一个经过训练的模型。使用时间序列预测预设,用自动ML对其进行训练。你知道吗
当我想运行预测时,我得到以下消息:
NumericalizeTransformer: Column AircraftModel contains categories not present at fit: {('42',)}. These categories will be set to NA prior to encoding.
.format(col, new_cats))
Column Operator contains categories not present at fit: {('US Airlines',)}. These categories will be set to NA prior to encoding.
.format(col, new_cats))
我运行forecast的代码如下:
def load_model():
global model
model_path = 'model.pkl'
model = joblib.load(model_path)
def run_forecast(data):
try:
y_query = data.pop('y_query').values
#y_query.fill(np.nan)
result = model.forecast(data, y_query)
except Exception as e:
result = str(e)
return json.dumps({"error": result})
forecast_as_list = result[0].tolist()
return forecast_as_list
input_sample = pd.DataFrame(data=[{'AircraftId': 'ATR-0001', 'FromDate': '2016-09-01T00:00:00.000Z', 'AircraftModel': '42', 'Operator': 'US Airlines', 'Country': 'Denmark', 'MonthOfYear': 9, 'y_query': 1.0}])
load_model()
forecast = run_forecast(input)
我得到了一个返回的结果,但它是相当糟糕的,我怀疑遗漏的功能列是罪魁祸首。你知道吗
在对模型运行推断之前,我是否应该手动进行一些预处理?你知道吗
目前没有回答
相关问题 更多 >
编程相关推荐