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Added script to pull historical stock data and resulting data files (1 per company). Added code to generate average price change per 1, 2 and 3-gram. Added code to output average price change per headline for VALIDATION dataset.

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This commit is contained in:
Woody Folsom
2012-04-20 21:22:54 -04:00
parent eec32b19c1
commit 6e3680426e
65 changed files with 360216 additions and 102 deletions
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35
test/net/woodyfolsom/cs6601/p3/dao/MySQLHeadlineDaoImplTest.java
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@@ -1,21 +1,23 @@
package net.woodyfolsom.cs6601.p3.dao;
import static org.junit.Assert.assertEquals;
import static org.junit.Assert.assertFalse;
import static org.junit.Assert.assertNotNull;
import static org.junit.Assert.assertTrue;
import net.woodyfolsom.cs6601.p3.svc.HeadlineService;
import org.junit.BeforeClass;
import org.junit.Ignore;
import org.junit.Test;
import org.springframework.context.ApplicationContext;
import org.springframework.context.support.ClassPathXmlApplicationContext;
import org.springframework.context.support.FileSystemXmlApplicationContext;
public class MySQLHeadlineDaoImplTest {
private static HeadlineService headlineSvc;
@BeforeClass
public static void setUp() {
ApplicationContext context=new ClassPathXmlApplicationContext(new String[]{"/AppContext.xml"});
ApplicationContext context=new FileSystemXmlApplicationContext(new String[]{"AppContext.xml"});
headlineSvc = (HeadlineService) context
.getBean("mySQLHeadlineSvc");
}
@@ -24,4 +26,29 @@ public class MySQLHeadlineDaoImplTest {
public void testSelect() {
assertNotNull(headlineSvc);
}
//Change this back to @Test to run it... but beware, it shuffles the datasets. Best done n times for n-fold cross validation.
@Ignore
public void testAssignRandomDatasets() {
int trainingPct = 80;
int testPct = 10;
int valPct = 10;
//assignment fails if character is ommitted from valPct (80% 10% 1% by accident)
assertFalse(headlineSvc.assignRandomDatasets(trainingPct,testPct,valPct/10));
//assignment succeeds if requested ratio is 8-1-1
assertTrue(headlineSvc.assignRandomDatasets(trainingPct,testPct,valPct));
int allCount = headlineSvc.getCount();
int trainingCount = headlineSvc.getCount(1);
int testCount = headlineSvc.getCount(2);
int valCount = headlineSvc.getCount(3);
assertEquals(trainingCount + testCount + valCount, allCount);
assertEquals((double)trainingCount/allCount,(double)trainingPct / 100.0,0.01);
assertEquals((double)testCount/allCount,(double)testPct / 100.0,0.01);
assertEquals((double)valCount/allCount,(double)valPct / 100.0,0.01);
}
}