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%
% As used by Kilpatrick, D. & Cameron-Jones, M. (1998). Numeric prediction
% using instance-based learning with encoding length selection. In Progress
% in Connectionist-Based Information Systems. Singapore: Springer-Verlag.
%
% Deleted "vendor" attribute to make data consistent with with what we
% used in the data mining book.
%
@relation 'cpu'
@attribute MYCT real

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@relation weather.symbolic

@attribute outlook {sunny, overcast, rainy}
@attribute temperature {hot, mild, cool}
@attribute humidity {high, normal}
@attribute windy {TRUE, FALSE}
@attribute play {yes, no}

@data
sunny,hot,high,FALSE,no

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/*
 * Hivemall: Hive scalable Machine Learning Library
 *
 * Copyright (C) 2015 Makoto YUI
 * Copyright (C) 2013-2015 National Institute of Advanced Industrial Science and Technology (AIST)
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *

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/*******************************************************************************
 * Copyright (c) 2010 Haifeng Li
 *   
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *  
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software

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/*
 * Hivemall: Hive scalable Machine Learning Library
 *
 * Copyright (C) 2015 Makoto YUI
 * Copyright (C) 2013-2015 National Institute of Advanced Industrial Science and Technology (AIST)
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *

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curl -s https://www.kaggle.com/c/titanic/data | pup 'tbody tr td a attr{href}' | awk '{print "https://kaggle.com" $1}' > urls.txt
# pup is required 
# https://github.com/ericchiang/pup

for f in `cat urls.txt`;
do
  echo "downloading file: ${f}" 
  wget -O `basename ${f}` https://www.kaggle.com/account/login?ReturnUrl=${f} --post-data "username=${KAGGLE_USER}&password=${KAGGLE_PASSWD}"
  echo
done

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ble to execute method public boolean hivemall.fm.FMPredictUDAF$Evaluator.iterate(org.apache.hadoop.hive.serde2.io.DoubleWritable,java.util.List,org.apache.hadoop.hive.serde2.io.DoubleWritable) throws org.apache.hadoop.hive.ql.metadata.HiveException  on object hivemall.fm.FMPredictUDAF$Evaluator@3272e5d6 of class hivemall.fm.FMPredictUDAF$Evaluator with arguments {1.3495872020721436:org.apache.hadoop.hive.serde2.io.DoubleWritable, []:java.util.ArrayList, 1.0:org.apache.hadoop.hive.serde2.io.DoubleWritable} of size 3
	at org.apache.hadoop.hive.ql.exec.FunctionRegistry.invoke(FunctionRegistry.java:1253)
	at org.apache.hadoop.hive.ql.udf.generic.GenericUDAFBridge$GenericUDAFBridgeEvaluator.iterate(GenericUDAFBridge.java:170)
	at org.apache.hadoop.hive.ql.udf.generic.GenericUDAFEvaluator.aggregate(GenericUDAFEvaluator.java:184)
	at org.apache.hadoop.hive.ql.exec.GroupByOperator.updateAggregations(GroupByOperator.java:641)
	at org.apache.hadoop.hive.ql.exec.GroupByOperator.processHashAggr(GroupByOperator.java:838)

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Hive history file=/mnt/hive/tmp/1/hive_job_log_eb8582f1-0cc1-4fdc-99fc-52b4896e5f74_1231952821.txt
**
** WARNING: time index filtering is not set!
** This query could be very slow as a result.
** If you used 'unix_timestmap' please modify your query to use TD_SCHEDULED_TIME instead
**   or rewrite the condition using TD_TIME_RANGE
** Please see http://docs.treasure-data.com/articles/performance-tuning#leveraging-time-based-partitioning
**
**
** WARNING: time index filtering is not set!

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Caused by: java.lang.NumberFormatException: empty String
	at sun.misc.FloatingDecimal.readJavaFormatString(FloatingDecimal.java:1020)
	at java.lang.Double.parseDouble(Double.java:540)
	at org.apache.hadoop.hive.serde2.objectinspector.primitive.PrimitiveObjectInspectorUtils.getDouble(PrimitiveObjectInspectorUtils.java:744)
	at hivemall.ftvec.trans.QuantitativeFeaturesUDF.evaluate(QuantitativeFeaturesUDF.java:91)
	at hivemall.ftvec.trans.QuantitativeFeaturesUDF.evaluate(QuantitativeFeaturesUDF.java:41)
	at org.apache.hadoop.hive.ql.exec.ExprNodeGenericFuncEvaluator._evaluate(ExprNodeGenericFuncEvaluator.java:166)
	at org.apache.hadoop.hive.ql.exec.ExprNodeEvaluator.evaluate(ExprNodeEvaluator.java:77)
	at org.apache.hadoop.hive.ql.exec.ExprNodeGenericFuncEvaluator$DeferredExprObject.get(ExprNodeGenericFuncEvaluator.java:77)
	at hivemall.tools.array.ConcatArrayUDF.evaluate(ConcatArrayUDF.java:86)