/
aster_functions.json
148 lines (148 loc) · 5.26 KB
/
aster_functions.json
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{
"name": "Analytical Functions",
"children": [
{
"name": "Time Series, Path and Attribution Analysis",
"children": [
{"name": "Attribution" },
{"name": "Cumulative Moving Average" },
{"name": "Dynamic time warping" },
{"name": "Discrete Wavelet Transform" },
{"name": "Discrete Wavelet Transform 2" },
{"name": "FrequentPaths" },
{"name": "Inverse Discrete Wavelet Transform" },
{"name": "Inverse Discrete Wavelet Transform 2" },
{"name": "Path_Analyzer" },
{"name": "Path_Generator" },
{"name": "Path_Start" },
{"name": "Path_Summarizer" },
{"name": "Symbolic Aggregate Approximation" },
{"name": "Sessionization" }
]
},
{
"name": "Pattern Matching with Teradata Aster nPath",
"children": [
{"name": "nPath" }
]
},
{
"name": "Statistical Analysis",
"children": [
{"name": "Approximate Distinct Count" },
{"name": "Approximate Percentile" },
{"name": "ConfusionMatrix" },
{"name": "Correlation" },
{"name": "Distribution Matching" },
{"name": "Exponential moving average" },
{"name": "Enhanced Histogram" },
{"name": "FMeasure" },
{"name": "Generalized linear model" },
{"name": "GLMPredict" },
{"name": "Histogram" },
{"name": "K-Nearest Neighbor" },
{"name": "Least Angle Regression" },
{"name": "Linear regression" },
{"name": "Percentile" },
{"name": "Principal Component Analysis" },
{"name": "Sample" },
{"name": "Simple Moving Average" },
{"name": "Support Vector Machines" },
{"name": "Volume-Weighted Average Price" },
{"name": "Weighted moving average" }
]
},
{
"name": "Text Analysis",
"children": [
{"name": "Latent Dirichlet Allocation Functions" },
{"name": "Levenshtein Distance" },
{"name": "Naive Bayes Text Classifier" },
{"name": "Named Entity Recognition" },
{"name": "nGram" },
{"name": "Part-of-speech Tagger" },
{"name": "Sentenizer" },
{"name": "Sentiment Extraction Functions" },
{"name": "Term Frequency - Inverse Document Frequency" },
{"name": "Text_Classifier" },
{"name": "Text_Parser" },
{"name": "TextChunker" },
{"name": "TextMorph" },
{"name": "TextTagging" },
{"name": "TextTokenizer" }
]
},
{
"name": "Cluster Analysis",
"children": [
{"name": "Canopy" },
{"name": "KMeans" },
{"name": "KMeansPlot" },
{"name": "Minhash" }
]
},
{
"name": "Naive Bayes",
"children": [
{"name": "NaiveBayesMap" },
{"name": "NaiveBayesReduce" },
{"name": "NaiveBayesPredict" }
]
},
{
"name": "Decision Trees",
"children": [
{"name": "Random Forest Functions" },
{"name": "Single Decision Tree Functions" }
]
},
{
"name": "Association Analysis",
"children": [
{"name": "Basket_Generator" },
{"name": "Collaborative Filtering" },
{"name": "Weighted-sum Recommender" }
]
},
{
"name": "Graph Analysis",
"children": [
{"name": "AllPairsShortestPath" },
{"name": "Betweenness" },
{"name": "Closeness" },
{"name": "EigenvectorCentrality" },
{"name": "LocalClusteringCoefficient" },
{"name": "LoopyBeliefPropagation" },
{"name": "nTree" },
{"name": "PageRank" }
]
},
{
"name": "Data Transformation",
"children": [
{"name": "Antiselect" },
{"name": "Apache Log Parser" },
{"name": "IdentityMatch" },
{"name": "IpGeo" },
{"name": "JSONParser" },
{"name": "Multicase" },
{"name": "MurmurHash" },
{"name": "OutlierFilter" },
{"name": "PSTParserAFS" },
{"name": "Pack" },
{"name": "Pivot" },
{"name": "Unpack" },
{"name": "Unpivot" },
{"name": "XMLParser" },
{"name": "XMLRelation" }
]
},
{
"name": "Visualization",
"children": [
{"name": "CfilterViz" },
{"name": "NpathViz" }
]
}
]
}