DBSCAN 返回 TypeError：无效的类型提升

Question

您好，我有一个看起来像这样的数据框。当我尝试运行 dbscan 来搜索异常值或异常时

"model = DBSCAN(eps = 0.4, min_samples = 5).fit(dataframe)"

它返回这个错误

“TypeError：无效的类型提升”

有没有办法解决这个问题？

    DateTime            Values
0   2020-12-18 15:44:00 554.0
1   2020-12-18 15:57:00 594.0
2   2020-12-18 15:58:00 513.0
3   2020-12-18 16:09:00 576.0
4   2020-12-18 16:10:00 654.0
... ... ...
881 2020-12-27 13:55:00 484.0
882 2020-12-27 14:09:00 491.0
883 2020-12-27 15:17:00 512.0
884 2020-12-27 15:54:00 529.0
885 2020-12-27 17:03:00 436.0

Answer 1

这是一个使用 DBSCAN 查找泰坦尼克号数据集中异常值的示例。

import seaborn as sns
import pandas as pd
titanic = sns.load_dataset('titanic')
titanic = titanic.copy()
titanic = titanic.dropna()
titanic['age'].plot.hist(
  bins = 50,
  title = "Histogram of the age variable"
)

 
from scipy.stats import zscore
titanic["age_zscore"] = zscore(titanic["age"])
titanic["is_outlier"] = titanic["age_zscore"].apply(
  lambda x: x <= -2.5 or x >= 2.5
)
titanic[titanic["is_outlier"]]

ageAndFare = titanic[["age", "fare"]]
ageAndFare.plot.scatter(x = "age", y = "fare")

 
from sklearn.preprocessing import MinMaxScaler
scaler = MinMaxScaler()
ageAndFare = scaler.fit_transform(ageAndFare)
ageAndFare = pd.DataFrame(ageAndFare, columns = ["age", "fare"])
ageAndFare.plot.scatter(x = "age", y = "fare")

 
from sklearn.cluster import DBSCAN
outlier_detection = DBSCAN(
  eps = 0.5,
  metric="euclidean",
  min_samples = 3,
  n_jobs = -1)
clusters = outlier_detection.fit_predict(ageAndFare)

clusters

from matplotlib import cm
cmap = cm.get_cmap('Accent')
ageAndFare.plot.scatter(
  x = "age",
  y = "fare",
  c = clusters,
  cmap = cmap,
  colorbar = False
)

顶部中心的两个点是两个异常值，它们以绿色突出显示。