我从Spark文档中读到了OHE条目,
单热编码将一列标签索引映射到一列二进制向量,最多只有一个单值.此编码允许期望连续特征(例如Logistic回归)的算法使用分类特征.
但遗憾的是,他们没有对OHE结果给出完整的解释.所以运行给定的代码:
from pyspark.ml.feature import OneHotEncoder, StringIndexer
df = sqlContext.createDataFrame([
(0, "a"),
(1, "b"),
(2, "c"),
(3, "a"),
(4, "a"),
(5, "c")
], ["id", "category"])
stringIndexer = StringIndexer(inputCol="category", outputCol="categoryIndex")
model = stringIndexer.fit(df)
indexed = model.transform(df)
encoder = OneHotEncoder(inputCol="categoryIndex", outputCol="categoryVec")
encoded = encoder.transform(indexed)
encoded.show()
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并得到了结果:
+---+--------+-------------+-------------+
| id|category|categoryIndex| categoryVec|
+---+--------+-------------+-------------+
| 0| a| 0.0|(2,[0],[1.0])|
| 1| b| 2.0| (2,[],[])|
| 2| c| 1.0|(2,[1],[1.0])|
| 3| a| 0.0|(2,[0],[1.0])|
| 4| a| 0.0|(2,[0],[1.0])|
| 5| c| 1.0|(2,[1],[1.0])|
+---+--------+-------------+-------------+
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我怎么能解释OHE的结果(最后一栏)?