本文整理了Java中water.fvec.Frame.naCount()方法的一些代码示例，展示了Frame.naCount()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。Frame.naCount()方法的具体详情如下：
包路径：water.fvec.Frame
类名称：Frame
方法名：naCount

Frame.naCount介绍

暂无

代码示例

代码示例来源：origin: h2oai/h2o-3

public void fillSimpleMeta(HashMap<String, Object> fm) {
 fm.put("DatasetName", _datasetName);
 fm.put("NRow", (double)_fr.numRows());
 fm.put("NCol", (double)_fr.numCols());
 fm.put("LogNRow", Math.log((double)fm.get("NRow")));
 fm.put("LogNCol", Math.log((double)fm.get("NCol")));
 fm.put("NACount", _fr.naCount());
 fm.put("NAFraction", _fr.naFraction());
 fm.put("NumberNumericFeat", (double)numberOfNumericFeatures());
 fm.put("NumberCatFeat", (double) numberOfCategoricalFeatures());
 fm.put("RatioNumericToCatFeat", Double.isInfinite((double) fm.get("NumberCatFeat"))     ? SQLNAN : (double) fm.get("NumberNumericFeat") / (double) fm.get("NumberCatFeat"));
 fm.put("RatioCatToNumericFeat", Double.isInfinite((double) fm.get("NumberNumericFeat")) ? SQLNAN : (double) fm.get("NumberCatFeat")     / (double) fm.get("NumberNumericFeat"));
 fm.put("DatasetRatio", (double) _fr.numCols() / (double) _fr.numRows());
 fm.put("LogDatasetRatio", Math.log((double) fm.get("DatasetRatio")));
 fm.put("InverseDatasetRatio", (double)_fr.numRows() / (double) _fr.numCols() );
 fm.put("LogInverseDatasetRatio", Math.log((double)fm.get("InverseDatasetRatio")));
 fm.put("Classification", _isClassification?1:0);
 fm.put("FeatWithNAs", (double)na_FeatureCount());
 fm.put("RowsWithNAs",(double)rowsWithNa());
 fm.put("NClass",(double)nClass());
 _statsSkewness = populateStats(StatsType.Skewness, _statsSkewness, fm);
 _statsKurtosis = populateStats(StatsType.Kurtosis, _statsKurtosis, fm);
 _statsCardinality = populateStats(StatsType.Cardinality, _statsCardinality, fm);
}

代码示例来源：origin: ai.h2o/h2o-automl

public void fillSimpleMeta(HashMap<String, Object> fm) {
 fm.put("DatasetName", _datasetName);
 fm.put("NRow", (double)_fr.numRows());
 fm.put("NCol", (double)_fr.numCols());
 fm.put("LogNRow", Math.log((double)fm.get("NRow")));
 fm.put("LogNCol", Math.log((double)fm.get("NCol")));
 fm.put("NACount", _fr.naCount());
 fm.put("NAFraction", _fr.naFraction());
 fm.put("NumberNumericFeat", (double)numberOfNumericFeatures());
 fm.put("NumberCatFeat", (double) numberOfCategoricalFeatures());
 fm.put("RatioNumericToCatFeat", Double.isInfinite((double) fm.get("NumberCatFeat"))     ? SQLNAN : (double) fm.get("NumberNumericFeat") / (double) fm.get("NumberCatFeat"));
 fm.put("RatioCatToNumericFeat", Double.isInfinite((double) fm.get("NumberNumericFeat")) ? SQLNAN : (double) fm.get("NumberCatFeat")     / (double) fm.get("NumberNumericFeat"));
 fm.put("DatasetRatio", (double) _fr.numCols() / (double) _fr.numRows());
 fm.put("LogDatasetRatio", Math.log((double) fm.get("DatasetRatio")));
 fm.put("InverseDatasetRatio", (double)_fr.numRows() / (double) _fr.numCols() );
 fm.put("LogInverseDatasetRatio", Math.log((double)fm.get("InverseDatasetRatio")));
 fm.put("Classification", _isClassification?1:0);
 fm.put("FeatWithNAs", (double)na_FeatureCount());
 fm.put("RowsWithNAs",(double)rowsWithNa());
 fm.put("NClass",(double)nClass());
 _statsSkewness = populateStats(StatsType.Skewness, _statsSkewness, fm);
 _statsKurtosis = populateStats(StatsType.Kurtosis, _statsKurtosis, fm);
 _statsCardinality = populateStats(StatsType.Cardinality, _statsCardinality, fm);
}