import breeze.linalg._pom.xml文件中需要调取哪个依赖

`import breeze.linalg._` 这行代码通常是在Scala项目中导入Breeze库的矩阵和向量运算相关的部分。Breeze是一个用于数值计算的 Scala 库，它提供了高性能的科学计算功能。要在`.pom.xml` 文件中添加对 Breeze 的依赖，你需要在`<dependencies>`标签内添加类似这样的内容：

<dependency>
    <groupId>org.scalanlp</groupId>
    <artifactId>breeze_2.11</artifactId>
    <version>0.14.0-M5</version> <!-- 请替换为你实际使用的版本 -->
</dependency>

这里，`groupId`通常是组织ID，`artifactId`对应于项目的名称，`breeze_2.11`表示这个库是针对 Scala 2.11编写的。请确保将`version`替换为你想要使用的Breeze库的实际版本。

如果你正在处理的是Maven项目，上述信息应该会帮助你在构建时正确地引用Breeze库。如果使用Sbt（Scala Build Tool），则会在build.sbt文件中配置依赖。

相关问题

error: value normal is not a member of breeze.linalg.DenseVector[Double]

This error message is indicating that you are trying to access a member called "normal" on an object of type breeze.linalg.DenseVector[Double], but this member does not exist on that type.

Without more context or code to review, it's difficult to provide a more specific explanation of what might be causing this issue. However, some possible causes could include:

- You may have misspelled the member name, or it may be defined on a different type.
- The object you are trying to access may not actually be a DenseVector[Double], but some other type that does not have a member called "normal".
- There may be a problem with your import statements or dependency setup, causing a missing member or type definition.

To resolve this error, you will need to review your code and ensure that you are accessing the correct member on the correct object. If you are still having trouble, you may need to provide additional context or seek further assistance from a colleague or online community.

代码如下： import breeze.numerics.round import org.apache.spark.sql.functions.col import org.apache.spark.sql.types.{DoubleType, IntegerType} import org.apache.spark.{SparkConf, SparkContext} import org.apache.log4j.{Level, Logger} import org.apache.spark.sql.DataFrame object Titanic_c { def main(args: Array[String]) = { Logger.getLogger("org").setLevel(Level.ERROR) val conf = new SparkConf().setAppName("Titanic_c").setMaster("local[2]") val sc = new SparkContext(conf) val spark = org.apache.spark.sql.SparkSession.builder .master("local") .appName("Titanic") .getOrCreate; val df = spark.read .format("csv") .option("header", "true") .option("mode", "DROPMALFORMED") .load("datasets/Titanic_s.csv") import spark.implicits._ df.withColumn("Pclass", df("Pclass").cast(IntegerType)) .withColumn("Survived", df("Survived").cast(IntegerType)) .withColumn("Age", df("Age").cast(DoubleType)) .withColumn("SibSp", df("SibSp").cast(IntegerType)) .withColumn("Parch", df("Parch").cast(IntegerType)) .withColumn("Fare", df("Fare").cast(DoubleType)) val df1 = df.drop("PassengerId").drop("Name").drop("Ticket").drop("Cabin") val columns = df1.columns val missing_cnt = columns.map(x => df1.select(col(x)).where(col(x).isNull).count) val result_cnt = sc.parallelize(missing_cnt.zip(columns)).toDF("missing_cnt", "column_name") result_cnt.show() import breeze.stats._ def meanAge(dataFrame: DataFrame): Double = { dataFrame .select("Age") .na.drop() .agg(round(mean("Age"), 0)) .first() .getDouble(0) } val df2 = df1 .na.fill(Map( "Age" -> meanAge(df1), "Embarked" -> "S")) val survived_count = df2.groupBy("Survived").count() survived_count.show() survived_count.coalesce(1).write.option("header", "true").csv("datasets/survived_count.csv") } }

我发现问题可能出在 `meanAge` 函数中的 `round(mean("Age"), 0)` 这句代码上。这个代码中的 `mean` 函数是 Spark SQL 中的函数，但是在 `breeze.stats` 包中也有一个名为 `mean` 的函数，这可能导致了混淆。为了解决这个问题，你可以尝试将 `mean` 函数改名为其他的变量名，例如：

def meanAge(dataFrame: DataFrame): Double = {
  val ageMean = dataFrame
    .select("Age")
    .na.drop()
    .agg(round(mean("Age"), 0))
    .first()
    .getDouble(0)
  ageMean
}

这样就将 `mean` 函数改名为了 `ageMean` 变量，并避免了与 `breeze.stats` 包中的函数重名的问题。希望对你有帮助！