 | Spreadsheet File Export |
| Spreadsheet File Export - Detail |
- . -
.WK1 files
export
import
.XLS files
export
import
.XLW files
- A -
accumulation indicators
accumulation/distribution indicators
Advanced System
advanced training criteria
alternative to discriminant function analysis
alternative to multiple regression
how to find the most important variables
sports prediction and handicapping
applications
ASCII files
export
import
attach files
Average Directional Movement indicator (ADX)
- B -
backpropagation
example
network architectures
training and stop training criteria
training graphs
Beginner's System
binary files
export
import
Bollinger Band indicators
- C -
C code
Calibration
candidates for survival
change indicators
| Change - Net Change (Momentum) |
| Change - Percent Change |
| Change - Rate of Change (Velocity) |
| Change - Rate of Rate of Change (Acceleration) |
| Commodity Channel Index (CCI) |
changes
| Changes Between Release 1.1 and 1.5 |
| Changes Between Release 1.5 and 2.0 |
| Changes Between Release 2.0 and 3.0 |
| Changes Between Release 3.0 and 4.0 |
| Program Changes |
classifications
how to obtain
coefficient of multiple determination
color
variable graphs
columns
combining files
Commodity Channel Index indicator
contribution factors module
correlation scatter plot
custom modules
- D -
daily change indicators
data entry
data ranking
| Race Handicapping Prenetwork |
| Race Handicapping Postnetwork |
| Race Handicapping Postnetwork - Detail |
| Race Handicapping Prenetwork - Detail |
data set colors
Datagrid
define inputs and outputs
training and stop training criteria
Directional Movement indicator (DX)
discriminant function analysis
displaying data
distribution by category
training graphs
DLL server
- E -
electric bill
error factor ranges
training graphs
| Backpropagation Error Factor Ranges Graphed Against Training Set Patterns |
| Backpropagation Error Factor Ranges Graphed Against Test Set Patterns |
examples
| Advanced System - Backpropagation - Lines |
| Advanced System - PNN - Spiral |
| Advanced System - GRNN - Saddle |
| Advanced System - Kohonen - Realty |
| Advanced System - Backpropagation - XOR |
exploded file
ASCII (text) files
binary files
spreadsheet files
extensions
- F -
ASCII (text)
binary
spreadsheet
ASCII (text)
binary
spreadsheet
formula
as a result of GMDH (polynomial) network
futures
- G -
Gaussian
General Regression Neural Network
architecture
genetic adaptive learning
genetic algorithm
glue files
GMDH
network architecture
training and stop training criteria
graph
training graphs
variable graphs
graph type
grid
GRNN
learning
network architecture
training and stop training criteria
training graphs
| GRNN Test Set Mean Square Error Graphed Against Generations |
| GRNN Test Set Mean Square Error Graphed Against Smoothing Factor |
network architecture
- H -
handicapping
hidden neurons
high low close graph
horse races
processing data
horse racing
hyperbolic tangent
scaling and activation functions
- I -
ASCII (text) files
binary files
spreadsheet files
importance of variables
index
indicators
accumulation
accumulation/distribution
Average Directional Movement (ADX)
Bollinger Band
change
| Change - Net Change (Momentum) |
| Change - Percent Change |
| Change - Rate of Change (Velocity) |
| Change - Rate of Rate of Change (Acceleration) |
| Commodity Channel Index (CCI) |
daily change
lagged moving average
life force
linear regression
moving average
moving average difference
| Mov Avg Diff - Exponential |
| Mov Avg Diff - Exponential & Lagged Exp |
| Mov Avg Diff - Linearly Weighted |
| Mov Avg Diff - Lin Wgt & Lagged Lin Wgt |
| Mov Avg Diff - Simple |
| Mov Avg Diff - Simple & Lagged Simple |
moving average of moving average difference
| Mov Avg of Mov Avg Diff - Exponential (MACD) |
| Mov Avg of Mov Avg Diff - Linearly Weighted |
| Mov Avg of Mov Avg Diff - Simple |
negative indexes
on balance
positive indexes
price trend
range
| Range - Highest minus Lowest Value |
| Range - Highest Value |
| Range - Lowest Value |
| Range - %R (Stochastic %K variation) |
relative strength index (RSI)
resistance indexes
resistance to advances
resistance to declines
stochastic
weighted moving average
William's
internal machine format files
export
import
- J -
jump connections
| Backpropagation Architecture - Jump Connections |
| Jump Connections |
| Network Architecture - Backpropagation |
- K -
Kohonen
network architecture
training and stop training criteria
training graphs
- L -
lagged moving average indicators
learning
GRNN
PNN
backpropagation
GMDH
GRNN
Kohonen
PNN
learning rate
legend
life force indicators
limitations
line statistics
linear
scaling and activation functions
linear correlation coefficient
| Correlation Coefficient r (Linear Correlation Coefficient) |
| Correlation Scatter Plot Detail |
| Correlation Scatter Plot Overview |
linear regression indicators
link
| Backpropagation Architecture - Standard Connections |
| Backpropagation Architecture - Jump Connections |
| Backpropagation Architecture - Recurrent Network |
| Backpropagation Architecture - Ward Networks |
| Link |
logistic
scaling and activation functions
- M -
market indicator package
market prediction
mean squared error
model
model complexity
momentum
monochrome
most important variables
moving average difference indicators
| Mov Avg Diff - Exponential |
| Mov Avg Diff - Exponential & Lagged Exp |
| Mov Avg Diff - Linearly Weighted |
| Mov Avg Diff - Lin Wgt & Lagged Lin Wgt |
| Mov Avg Diff - Simple |
| Mov Avg Diff - Simple & Lagged Simple |
moving average indicators
moving average of moving average difference indicators
| Mov Avg of Mov Avg Diff - Exponential (MACD) |
| Mov Avg of Mov Avg Diff - Linearly Weighted |
| Mov Avg of Mov Avg Diff - Simple |
- N -
negative indexes - indicators
backpropagation
GMDH
GRNN
Kohonen
PNN
neural network application
NeuroShell 2
program changes
| Changes Between Release 1.1 and 1.5 |
| Changes Between Release 1.5 and 2.0 |
| Changes Between Release 2.0 and 3.0 |
| Changes Between Release 3.0 and 4.0 |
| Program Changes |
- O -
on balance indicators
optimization
output file
printing
- P -
PNN
learning
network architectures
training and stop training criteria
training graphs
polynomial networks
positive indexes - indicators
prediction
application tips
predictions
how to obtain
price trend indicators
printouts
Probabilistic Neural Networks
network architecture
problem type
Beginner's System
process control
processing data files
production set
program changes
| Changes Between Release 1.1 and 1.5 |
| Changes Between Release 1.5 and 2.0 |
| Changes Between Release 2.0 and 3.0 |
| Changes Between Release 3.0 and 4.0 |
| Program Changes |
- R -
R squared
race handicapping
| Race Handicapping Prenetwork |
| Race Handicapping Postnetwork |
| Custom - Postnetwork |
| Custom - Prenetwork |
| Race Handicapping Postnetwork - Detail |
| Race Handicapping Prenetwork - Detail |
range indicators
| Range - Highest minus Lowest Value |
| Range - Highest Value |
| Range - Lowest Value |
| Range - %R (Stochastic %K variation) |
real estate
recurrent networks
relative strength index indicators
resistance indexes - indicators
resistance to advances indicators
resistance to declines indicators
rows
RSI indicators
Rules
runtime facilities
| Runtime Facilities |
| DLL Server Overview |
| How to Use the DLL Server |
| Source Code Generator Overview |
| How to Use the Source Code Generator |
- S -
scatter graph symbol
selection criterion
self organizing map
set minimum and maximum values
sine
slab
| Backpropagation Architecture - Standard Connections |
| Backpropagation Architecture - Jump Connections |
| Backpropagation Architecture - Recurrent Network |
| Backpropagation Architecture - Ward Networks |
| Slab |
smart training criteria
smoothing factor
| Apply PNN Network |
| Apply GRNN Network |
| GRNN Test Set Mean Square Error Graphed Against Smoothing Factor |
| PNN Incorrect Patterns Graphed Against Smoothing Factor |
| Smoothing Factor |
source code generator
sports prediction
spreadsheet files
export
import
spreadsheet program
squared error
standard connections
statistics
training
| Backpropagation Learning |
| Kohonen Learning |
| PNN Learning |
| PNN Genetic Adaptive Learning |
| GRNN Learning |
| GRNN Genetic Adaptive Learning |
| GMDH Learning |
stochastic indicators
stock
stock market
application tips (Tutorial example two)
stock market prediction
stocks
backpropagation
GMDH
styles
symbol translate
| Symbol Translate Input Files |
| Symbol Translate Output Files |
| Symbol Translate Input Files - Detail |
| Symbol Translate Output Files - Detail |
- T -
test set extract
text files
export
import
time series data
graphing
titles
training
GRNN
PNN
training and stop training criteria
backpropagation
GMDH
training graphs
training set
training statistics
| Backpropagation Learning |
| Kohonen Learning |
| PNN Learning |
| PNN Genetic Adaptive Learning |
| GRNN Learning |
| GRNN Genetic Adaptive Learning |
| GMDH Learning |
transfer information to another problem
backpropagation
| Backpropagation Architecture - Standard Connections |
| Backpropagation Architecture - Jump Connections |
| Backpropagation Architecture - Ward Networks |
| Network Architecture - Backpropagation |
GMDH
GRNN
Kohonen
PNN
- U -
useful hints
GMDH
- V -
variable graphs
viewer
Visual Basic code
- W -
Ward networks
weighted moving average indicators
weights
weights in link
William's indicators
winning neuron
word processor files
export
import
- X -