AzureML时间序列模型无法识别inferen上的特征值

2024-03-28 09:23:28 发布

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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


Tags: todatamodelasnotloadcolumnresult