public TestPredictions Decide(TrainerHelper container, DataTable table, string inputId)
{
if (container.trainer == null)
{
return(null);
}
var symbols = container.codification.Apply(table);
container.columnNamesArray =
table.Columns.Cast <DataColumn>().Select(x => x.ColumnName).Where(s => s != inputId).ToArray();
var columnOrdinal = table.Columns[inputId].Ordinal;
double[][] tempInputs = symbols.ToJagged(container.columnNamesArray);
double[][] inputs = new double[tempInputs.Length][];
var foo = new TestPredictions();
var predictions = new List <KeyValuePair <string, double> >();
var correct = 0;
var incorrect = 0;
var contents = new StringBuilder();
foreach (DataRow x in table.Rows)
{
var values = x.ItemArray.Select(c => c.ToString()).ToList();
var answer = values[columnOrdinal];
values.RemoveAt(columnOrdinal);
var prediction = this.Decide(container, values.ToArray(), inputId);
contents.Append(string.Format("{0},{1},{2}" + Environment.NewLine, answer, prediction.Key, prediction.Value));
if (answer == prediction.Key)
{
correct++;
}
else
{
if (prediction.Value > 75)
{
incorrect++;
}
}
}
File.WriteAllText(@"c:\temp\hack1.txt", contents.ToString());
int[] outputs = symbols.ToArray <int>(inputId);
foo.Total = table.Rows.Count;
foo.Correct = correct;
foo.Incorrect = incorrect;
foo.Contents = contents.ToString();
return(foo);
}
public TestPredictions Decide(TrainerHelper container, DataTable table, string inputId)
{
if (container.trainer == null)
{
return(null);
}
var symbols = container.codification.Apply(table);
container.columnNamesArray =
table.Columns.Cast <DataColumn>().Select(x => x.ColumnName).Where(s => s != inputId).ToArray();
var columnOrdinal = table.Columns[inputId].Ordinal;
double[][] tempInputs = symbols.ToJagged(container.columnNamesArray);
double[][] inputs = new double[tempInputs.Length][];
for (var i = 0; i < tempInputs.Length; i++)
{
var flattened = this.ExpandRow(container.codification, tempInputs[i], columnOrdinal);
inputs[i] = flattened;
}
int[] outputs = symbols.ToArray <int>(inputId);
var foo = new TestPredictions();
var predictions = new List <KeyValuePair <string, double> >();
//foo.Predictions = predictions;
var predicted = container.decisionTree.Decide(inputs);
var predictedValues = container.codification.Revert(inputId, predicted);
//var confidences = container.trainer.Probabilities(inputs);
var correct = 0;
var incorrect = 0;
var contents = new StringBuilder();
for (var i = 0; i < predicted.Length; i++)
{
var predictedAsInt = predicted[i];
var actualValue = outputs[i];
var predictedValue = predictedValues[i];
//var c = confidences[i];
var p = 0.0;
//if (c.Length > 0)
{
//p = c[0];
}
p = p * 100;
if (predictedAsInt == actualValue)
{
correct++;
}
else
{
if (p > 75)
{
incorrect++;
}
}
var a = new KeyValuePair <string, Double>(predictedValue, p);
predictions.Add(a);
contents.Append(string.Format("{0},{1},{2}" + Environment.NewLine, actualValue, predictedValue, p));
}
foo.Total = predicted.Length;
foo.Correct = correct;
foo.Incorrect = incorrect;
foo.Contents = contents.ToString();
return(foo);
}
